Cloud Native

Cloud Native Data Jobs

270 jobs found

Today

Senior Databricks Data Engineer

CGI Group, Inc. Miami, FL

Miami, FL

Today

$92k - $204k/yr Full time Senior Azure Azure Databricks

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Job Description

Senior Databricks Data Engineer role focused on building scalable enterprise ETL/ELT pipelines end to end.

Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines using Databricks, Apache Spark, Python/PySpark, and SQL
Build batch and incremental data integration pipelines from files, databases, and enterprise data sources
Create reusable, maintainable data processing solutions
Optimize Spark workloads for performance, scalability, reliability, and cost efficiency
Implement data quality controls, reconciliation, monitoring, and error handling
Own the complete engineering lifecycle: requirements analysis, solution design, technical review, implementation, and deployment
Prepare and present technical solution designs for architecture and engineering review
Incorporate review feedback and implement approved designs
Make appropriate technical decisions and proactively resolve engineering challenges
Take accountability for deliverables, quality, timelines, and production readiness
Develop complex SQL transformations for cleansing, enrichment, and aggregation
Design and maintain curated datasets, dimensional models, and reporting views
Support enterprise analytics, reporting, and downstream data consumers
Implement and maintain pipeline orchestration using Airflow, Databricks Workflows, or comparable tools
Apply CI/CD practices for version control, automated deployment, and release management
Troubleshoot pipeline failures and production performance issues
Collaborate with data architects, integration teams, engineering teams, and business stakeholders
Document technical designs, implementation decisions, and operational procedures

Requirements

Minimum 5 years of relevant experience in data engineering, data integration, or related disciplines
Strong, recent hands-on development experience with Databricks
Proven experience designing, building, and implementing production ETL/ELT pipelines
Advanced proficiency in Apache Spark, PySpark, and Python with demonstrated hands-on engineering experience
Strong SQL skills, including complex joins, window functions, data transformations, and query performance tuning
Experience with at least one major cloud platform: AWS, Azure, or Google Cloud Platform (GCP)
Experience with workflow orchestration tools such as Apache Airflow, Databricks Workflows, or equivalent platforms
Experience with CI/CD practices, source control, and automated deployment of data pipelines
Demonstrated ability to independently own the full development lifecycle, including solution design, technical review, implementation, and production support
Proven ability to evaluate requirements, make sound technical design decisions, and implement approved solutions
Strong problem-solving skills with a track record of independent execution, accountability, and ownership in fast-paced environments

Technologies

Databricks
Apache Spark
Python
PySpark
SQL
Airflow
Databricks Workflows
CI/CD
AWS
Azure
Google Cloud Platform (GCP)
Delta Lake
Unity Catalog
REST API

Nice to Haves

Calling external APIs from Databricks notebooks, including REST API integration, authentication, request handling, and ingestion of API responses (building or exposing APIs is not required)
Streaming and event driven data processing
Delta Lake and medallion architecture
Unity Catalog, governance, and lineage
Metadata driven and reusable pipeline frameworks
Enterprise scale Databricks implementations
Experience with complex enterprise data integration environments
Spark performance tuning and cost optimization
Batch and incremental data processing
Data quality, reconciliation, monitoring, and observability
Data warehousing, fact/dimension modeling, and curated data layers
Production troubleshooting and operational reliability
Technical documentation and design review participation

Benefits

Competitive compensation
Comprehensive insurance options
Matching contributions through the 401(k) plan and the share purchase plan
Paid time off for vacation, holidays, and sick time
Paid parental leave
Learning opportunities and tuition assistance
Wellness and Well being programs

Location: Miami, FL (hybrid)

Salary: USD 91,800 - 203,800 per yearly

Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related field

Additional info: CGI anticipates accepting applications through November 13, 2026. Compensation range estimate for the U.S.: $91,800.00 - $203,800.00.

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Today

Mid-Level Full-Stack AI Engineer

CGI Group, Inc. Knoxville, TN

Knoxville, TN

Today

$80k - $110k/yr Full time Backend Developer Manager AI

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Job Description

CGI is hiring a mid-level full-stack AI engineer to design, build, and deploy production AI applications using modern full-stack tooling and generative AI.

Responsibilities

Lead end-to-end design, development, and deployment of AI-powered applications spanning backend services, APIs, data pipelines, model integrations, and user-facing interfaces
Architect, build, and maintain scalable, secure, high-performance backend services using Python; develop responsive front-end applications using Angular
Design and implement generative AI, LLM-based solutions, NLP, document classification, OCR, and conversational AI
Drive machine learning work including inference, training, fine-tuning, and optimization for reliable production capabilities
Develop and optimize RESTful APIs, system integrations, and database solutions to support interoperability, performance, and scalability
Implement and maintain CI/CD pipelines and containerized deployments using Docker, Kubernetes, and cloud technologies
Partner with product managers, data scientists, UI/UX designers, and engineering teams to translate business needs into technical designs and AI feature delivery
Lead technical development of client-focused AI use cases leveraging CGI’s AI Platform, from solution design through production deployment
Monitor, troubleshoot, and optimize production applications to ensure availability, security, reliability, performance, and operational efficiency
Mentor junior engineers and participate in architecture and design reviews; guide teams and champion software engineering best practices

Requirements

Bachelor’s degree in Computer Science, Artificial Intelligence, Software Engineering, or a related technical discipline, or equivalent practical experience
2+ years of professional full-stack development experience with strong Python backend skills and Angular frontend skills
2+ years of hands-on experience building AI-powered products involving generative AI, NLP, document classification, chatbots, OCR, or related intelligent automation
Demonstrated experience with machine learning concepts, LLM inference, model integration, and deploying AI-enabled applications
Strong experience designing and developing RESTful APIs, integrating distributed components, and applying software architecture and system design principles
Hands-on experience with Docker and Kubernetes, including production deployment and container orchestration concepts
Proficiency with relational and non-relational databases, including design, querying, performance tuning, and optimization
Experience leveraging cloud platforms such as Microsoft Azure or Google Cloud Platform (GCP) to develop, deploy, manage, and scale AI applications
Knowledge of secure development practices, data privacy regulations, compliance requirements, and responsible AI principles
Strong analytical, troubleshooting, communication, and collaboration skills, including ownership of deliverables and the ability to guide junior team members in a fast-paced environment

Technologies

Python, Angular
Machine learning, generative AI, large language model (LLM)
Natural language processing (NLP), document classification, optical character recognition (OCR), conversational AI
RESTful APIs, CI/CD, Docker, Kubernetes
Cloud technologies
Relational databases, non-relational databases
Microsoft Azure, Google Cloud Platform (GCP)
LangChain, Hugging Face
Retrieval-augmented generation (RAG), vector databases, embeddings, prompt engineering
AI agent architectures, MLOps
GitHub Actions, Azure DevOps, Microsoft Azure AI services, Google Cloud AI services

Strongly Preferred

Experience building production-grade applications using LLM frameworks, orchestration libraries, or AI development tools such as LangChain and Hugging Face
Hands-on RAG implementation, including vector databases, embeddings, prompt engineering, or AI agent architectures
Experience with fine-tuning, model evaluation, MLOps, and monitoring AI models in production
Experience building automated CI/CD pipelines, testing frameworks, and deployment workflows using GitHub Actions, Azure DevOps, or similar tools
Experience designing and deploying AI solutions using Microsoft Azure AI services, Google Cloud AI services, or related cloud-native AI technologies
Demonstrated ability to lead technical feature development, mentor engineers, contribute to architecture decisions, and deliver customer-focused AI solutions

Location

Knoxville, TN (onsite)
May be based in any CGI office in the United States, with Knoxville, TN as the preferred location

Compensation

USD 79,600 - 109,500 per year

Benefits

Competitive compensation
Comprehensive insurance options
Matching contributions through the 401(k) plan and the share purchase plan
Paid time off for vacation, holidays, and sick time
Paid parental leave
Learning opportunities and tuition assistance
Wellness and Well being programs

Contingencies and Eligibility

U.S. offers of employment are contingent on successful completion of a background investigation
Some background investigations may include a credit check based on role and/or federal government security clearance requirements
Qualified applicants with arrests and conviction records will be considered in accordance with local regulations and ordinances

Equal Opportunity and Accommodation

Employment consideration is provided without regard to race, ethnicity, ancestry, color, sex, religion, creed, age, national origin, citizenship status, disability, pregnancy, medical condition, military and veteran status, marital status, sexual orientation, gender identity or expression, familial status or responsibilities, reproductive health decisions, political affiliation, genetic information, or physical attributes
CGI provides reasonable accommodations to qualified individuals with disabilities
To request an accommodation to apply in the U.S., email US_Employment_Compliance@cgi.com and reference the Position ID

CGI is required in some jurisdictions to include a reasonable estimate of the compensation range, which may vary based on skill set, level, experience, relevant training, and licensure or certifications.

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Today

Lead Generative AI Engineer

CGI Group, Inc. Reston, VA

Reston, VA

Today

$81k - $268k/yr Full time Manager Agentic Ai Ai Agent

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Job Description

Join CGI Group, Inc. in Reston, VA (onsite) to lead the architecture and development of Generative AI and agentic AI solutions. This role blends hands-on engineering with technical leadership, taking initiatives from proof of concept to secure, reliable production systems across an enterprise environment. Salary range: USD 80,600 - 267,800 per year. Minimum experience: 6+ years.

What you’ll work on

Lead the architecture and development of Generative AI, Retrieval-Augmented Generation (RAG), and agentic AI solutions
Build and scale AI applications from prototype through production deployment
Develop RAG pipelines, multi-agent workflows, APIs, and microservices
Design secure, scalable integrations across cloud, data, and enterprise platforms
Implement responsible AI guardrails covering privacy, security, bias, and human oversight
Evaluate AI solutions for quality, hallucinations, latency, reliability, and cost

Engineering leadership and delivery

Establish engineering standards, perform code reviews, and mentor technical teams
Deliver CI/CD and operational readiness with MLOps, LLM Ops, automated testing, monitoring, and observability
Partner with business, architecture, security, and data teams to translate requirements into technical solutions
Create reusable AI components, frameworks, and development standards to accelerate delivery

Required qualifications

6+ years of experience in software engineering, data engineering, machine learning engineering, or a related field
Proven experience deploying and supporting AI or machine learning solutions in production
Strong experience with Generative AI, large language models, RAG, prompt engineering, and context engineering
Advanced Python proficiency
Experience with GCP, AWS, Azure, or a comparable cloud platform
Experience with APIs, microservices, containerization, Docker, and Kubernetes
Knowledge of CI/CD, ML Ops, LLM Ops, monitoring, and AI evaluation practices
Ability to lead technical teams and communicate with senior stakeholders

Preferred qualifications

Experience with Google Cloud Platform and Vertex AI
Experience with Palantir Foundry
Experience building AI agents using Lang Graph, Agent Development Kit, or custom frameworks
Knowledge of traditional machine learning techniques, including classification, regression, and clustering
Experience designing hybrid AI solutions balancing accuracy, performance, latency, and cost

Technologies

Python
Google Cloud Platform, Vertex AI
AWS, Azure
Docker, Kubernetes
Retrieval-Augmented Gen. (RAG)
LangGraph, Lang Graph
Amazon CloudFront
Palantir Foundry
Agent Development Kit

Compensation and benefits

Competitive compensation (USD 80,600 - 267,800 per year)
Comprehensive insurance options
Matching contributions through the 401(k) plan and the share purchase plan
Paid time off for vacation, holidays, and sick time
Paid parental leave
Learning opportunities and tuition assistance
Wellness and Wellbeing programs

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2d ago

Staff Machine Learning Engineer

Integral Ad Science, Inc. San Francisco, CA

San Francisco, CA

2d ago

$135k - $232k/yr Full time Application Security Artificial Intelligence Automation

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Job Description

Integral Ad Science, Inc. is hiring a Staff Machine Learning Engineer for the Data Science Team to lead and oversee large-scale AI/ML systems and architectures that support business predictions across the open web, social networks, video, and mobile applications. This onsite role in San Francisco includes technical leadership and end-to-end ownership from CI/CD through production deployment.

Responsibilities

Set the architectural vision and own system design for core AI/ML-based services.
Serve as technical lead for multi-quarter initiatives, guiding work from inception through global deployment.
Design and build large-scale deep learning infrastructure and platforms for distributed model training, focused on low-latency and high availability at enterprise scale.
Collaborate with Product Management, Core Engineering, and executive stakeholders to align ML capabilities with business strategy.
Convert abstract product requirements into concrete technical designs.
Mentor and guide senior and mid-level data scientists and engineers.
Define standard methodologies, establish code quality expectations, and lead architecture design reviews.
Work with large-scale AI training infrastructure components, including accelerators, network fabrics, CUDA, NCCL, and RDMA, as well as big data ecosystems such as Databricks, Spark, Kubernetes, Kafka, and Prometheus.
Design, develop, and support robust CI/CD pipelines for AI/ML services to move models reliably from research into production endpoints.

Requirements

PhD or Master’s degree in a technical field (for example, computer science, mathematics, or statistics) or equivalent years of experience.
7+ years of machine learning experience in industry with a demonstrated record at Lead, Principal, or Staff level.
Deep expertise in designing complex machine learning systems, ranking infrastructures, and data pipelines capable of massive throughput.
Production-hardened experience with frameworks including PyT orch, JAX, or T ensorFlow.
Strong production-grade programming skills in Python, Go, Java, or C++, with a deep understanding of software design principles and algorithms.
Proven ability to operate effectively in ambiguous environments and drive large unstructured problems to technical resolution.
A history of collaborating with, elevating, and mentoring engineering talent.

Technologies

PyT orch, JAX, T ensorFlow
Python, Go, Java, C++
CUDA, NCCL, RDMA
Databricks, Spark, Kubernetes, Kafka, Prometheus

Benefits

Paid time off
Health insurance (medical, dental, vision)
PPO, HSA and FSA options
401k with employer matching contributions
Eligible for an annual bonus and/or other incentive plans

Pay and Location

Location: San Francisco, CA (onsite)

Salary: USD 135,100 - 231,600 per year

IAS Pay Transparency:

Primary Location: US - New York, NY
Primary Location Base Pay Range: $135,100.00 - $231,600.00 Annual
Additional Locations: US - Chicago, IL; US - San Francisco, CA
Additional Locations Pay Range: 119,000.00 - 204,000.00 USD Annual

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2d ago

Machine Learning Engineer 5 (Senior Manager, IC)

Information Technology Senior Management Forum New York, NY

New York, NY

2d ago

$230k - $262k/yr Full time Backend Developer Manager Artificial Intelligence

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Job Description

Build and scale production-grade machine learning systems across modeling, data pipelines, and deployment practices.

Responsibilities

Design, build, and/or deliver ML models and components to address real-world business needs in collaboration with Product and Data Science
Develop and scale large multi-tenant platforms for ML model training and/or serving at scale
Guide ML infrastructure decisions using ML modeling expertise, including model and feature selection, training, hyperparameter tuning, dimensionality considerations, bias-variance tradeoffs, and validation
Solve complex problems through application code development, ML model development and validation, plus automated testing and deployment
Work in a cross-functional Agile team to create and enhance software supporting big data and ML applications
Retrain, maintain, and monitor machine learning models in production
Leverage and/or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale
Construct optimized data pipelines to feed ML models
Apply CI/CD best practices, including test automation and monitoring, to support successful deployment of ML models and application code
Manage code to reduce vulnerabilities, govern models from a risk perspective, and follow best practices for Responsible and Explainable AI
Use Python, Scala, or Java to implement ML and platform components

Requirements

Bachelor’s degree or higher in Computer Science, Machine Learning, or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
At least 6 years of programming experience with Python, Java, Golang, or C++
At least 6 years of ML experience with industry-standard frameworks PyTorch or Tensorflow, plus libraries (Pandas, NumPy, Scikit-learn)
At least 6 years operating large-scale distributed systems (e.g., Spark, Ray) to prepare AI/ML data
At least 4 years deploying and operating ML solutions in production and running production services in the cloud (AWS, GCP, Azure), using Kubernetes for large-scale containerized ML systems

Technologies

Python, Scala, Java, Golang, C++
PyTorch, Tensorflow
Pandas, NumPy, Scikit-learn
Spark, Ray
AWS, GCP, Azure
Kubernetes

Preferred Qualifications

Master’s or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field
5+ years optimizing ML algorithms, configurations, and infrastructure
5+ years following software development best practices (source control, testing, code reviews, CI/CD)
5+ years building resilient software with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and incident response plan preparation
5+ years applying ML techniques (supervised, semi-supervised, unsupervised, reinforcement learning) across model types (Regression, Classification, Clustering), architectures (RNNs, CNNs, LSTMs, Transformers), and training concepts (loss function, hyperparameters, regularization), plus evaluating accuracy and diagnosing issues (underfitting, overfitting)
5+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
Ability to communicate complex technical and ML concepts clearly to varied audiences

Location: New York, NY (onsite)

Salary: USD 229,900 - 262,400 per yearly

Minimum experience: 4 years

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2d ago

Machine Learning Engineer 5, Senior Manager - Intelligent Foundations and Experiences (IFX)

Information Technology Senior Management Forum McLean, VA

McLean, VA

2d ago

$230k - $262k/yr Full time Backend Developer Manager Ai Ml

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Job Description

In this senior leadership Machine Learning Engineer role, you will help design and scale AI and machine learning capabilities, from model development through production training and monitoring. The position supports Capital One-focused implementation work and involves building multi-tenant ML platforms alongside Product and Data Science teams.

This onsite role is based in McLean, VA and targets candidates with strong experience across ML modeling, distributed data systems, and cloud deployment practices.

Role focus

Design, build, and deliver ML models and components to address business problems in collaboration with Product and Data Science teams
Build and scale large multi-tenant platforms for ML model training and serving at scale
Use ML modeling knowledge to guide infrastructure decisions, including model choice, data and feature selection, training approach, hyperparameter tuning, dimensionality, and bias/variance tradeoffs and validation
Solve complex engineering problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
Retrain, maintain, and monitor models in production
Leverage or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale
Construct optimized data pipelines that feed ML models
Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to support successful deployment of ML models and application code
Maintain well-managed code to reduce vulnerabilities, ensure risk-governed model usage, and follow best practices in Responsible and Explainable AI
Work within an Agile, cross-functional team to create and enhance software enabling big data and ML applications

Programming and tooling

Use Python, Scala, or Java for development
Technologies include PyTorch, Tensorflow, Pandas, NumPy, Scikit-learn
Distributed systems for data preparation include Spark and Ray
Cloud and orchestration: AWS, GCP, Azure, and Kubernetes
CI/CD practices are expected for deployment workflows

Minimum qualifications

Bachelor’s degree or higher in Computer Science, Machine Learning, or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
At least 6 years of experience programming with Python, Java, Golang, or C++
At least 6 years of Machine Learning experience using PyTorch or Tensorflow and libraries such as Pandas, NumPy, and Scikit-learn
At least 6 years using and operating large scale distributed systems like Spark and Ray for AI or ML data preparation
At least 4 years deploying and operating ML solutions in production, operating production services in the cloud (AWS, GCP, Azure), and using Kubernetes to manage large scale containerized ML systems

Preferred qualifications

Master’s or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or a related field
+2 years experience building production RAG pipelines (chunking, embeddings, vector indexing, graph RAG, or fine-tuning)
+2 years experience leveraging agentic patterns (Tool Calling, ReAct loops, Plan-and-Execute, Multi-Agent Collaboration)
+2 years with LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel) and model APIs (OpenAI, Anthropic, Bedrock, Ollama, Hugging Face)
+2 years of experience building agentic AI systems and agentic workflows
+2 years developing AI and ML algorithms or technologies (e.g., LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang
+2 years experience right-sizing models, instance counts, and hardware types based on requirements (context length, token inputs, token outputs)
5+ years optimizing ML algorithms, configurations, and infrastructure
5+ years following software development best practices including source control, testing, code reviews, and CI/CD
5+ years building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and incident response planning
5+ years working with ML techniques (Supervised, semi-supervised, and unsupervised learning, reinforcement learning) and model types (Regression, Classification, Clustering)
5+ years with model architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and evaluating model accuracy
5+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
Ability to communicate complex technical and machine learning concepts to a variety of audiences

Compensation and benefits

Salary: USD 229,900 - 262,400 per year for the McLean, VA location (Machine Learning Engineer 5)
Salary: USD 209,000 - 238,500 per year for Richmond, VA (Machine Learning Engineer 5)
Eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI)
Capital One offers comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being

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2d ago

Machine Learning Engineer

Adidev Technologies Inc Seattle, WA

Seattle, WA

2d ago

Full time Ai Ml Artificial Intelligence Automation

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Job Description

Adidev Technologies Inc is looking for a Machine Learning Engineer to help deploy advanced machine learning models with a special focus on Generative AI. You will work from modeling through deployment and monitoring, building AI-driven solutions that translate complex data into practical outcomes.

This is an onsite role in Seattle, WA, with compensation that aligns with experience and market value. The team also supports your move with paid relocation and provides remote assistance even when you are not onsite. There are regular salary reviews tied to your performance and the market. Beyond compensation, Adidev emphasizes long-term growth through structured guidance and project support.

How you’ll guide AI from idea to production

Architect and refine sophisticated ML models and algorithms to convert complex datasets into actionable solutions.
Own the data modeling lifecycle, starting from understanding business requirements through deployment and monitoring.
Perform comprehensive data analysis, including preprocessing, feature engineering, and applying Generative AI algorithms to develop novel solutions.
Lead cross-functional collaboration to integrate Generative AI models into offerings, improving product capabilities and user experiences.
Use advanced analytical techniques to identify trends, anomalies, and opportunities for improvement across large datasets.
Apply data preprocessing, feature engineering, and algorithm optimization to improve both accuracy and efficiency.
Conduct exploratory data analysis to extract insights that influence strategic decisions.
Stay current on ML trends and best practices, including AutoML, MLOps, and interpretability frameworks.
Promote compliance with industry standards and regulatory requirements, with an emphasis on ethical AI.

What you bring

A degree in Computer Science, Engineering, Statistics, or a related technical field.
Demonstrable experience across one or more AI domains such as machine learning, deep learning, NLP, computer vision, and reinforcement learning.
Demonstrable experience with Generative AI models and frameworks used in industry settings, such as GANs or Transformers.
Practical experience with SQL/NoSQL databases, data visualization tools, and version control systems.
Strong fundamentals in algorithmic complexity and data structure optimization.
Excellent problem-solving, collaboration, and communication skills.
Ability to develop and implement cutting-edge ML models, with a particular focus on Generative AI applications including text generation, image synthesis, and creative AI.
Experience applying the latest research findings in AI, especially in Generative AI, to drive innovation.
Python proficiency and experience with ML libraries such as TensorFlow, PyTorch, and scikit-learn.
Strong background in cloud computing and big data platforms (AWS, Azure, GCP), including hands-on work with cloud-based ML services and serverless architectures.
Familiarity with DevOps for AI, including Docker, Kubernetes, CI/CD pipelines, and MLOps.
Ability to facilitate knowledge sharing and best practices in AI/ML, particularly around Generative AI.
Commitment to ethical guidelines and data privacy standards for AI implementations.

Tools you’ll likely work with

Python, TensorFlow, PyTorch, scikit-learn
GANs, Transformers
SQL, NoSQL
AWS, Azure, GCP
Docker, Kubernetes

How Adidev will support your growth

Teaching and Development: guidance to help you grow into a strong consultant delivering high-quality solutions to end clients.
Custom Support: access to multiple teams, including Development Managers and Tech Subject Matter Experts.
Project Placement: a market-expertise team supports you in securing and succeeding in projects with clients.
Career Growth: opportunities to build industry experience and advance your technical journey.

Diversity and equal opportunity

Adidev Technologies Inc. is a staunch advocate of diversity and equal opportunity. They warmly welcome applications from candidates of all backgrounds, experiences, and walks of life.