Engineering

Engineering Data Jobs

72 jobs found

Today

Lead Applied AI Engineer II

Deloitte New York, NY

New York, NY

Today

$119k - $244k/yr Full time Artificial Intelligence Azure Openai Cloud Operations

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Job Description

This senior, hands-on AI engineering position is located onsite in New York, NY. It focuses on delivering high-visibility software across multiple languages and frameworks, while mentoring teams and collaborating cross-functionally to design, develop, and deploy advanced AI solutions.

Responsibilities

Own engineering outcomes aligned with customer and business goals, delivering lean, high-quality designs that solve complex problems.
Act as the technical advocate for products, ensuring code integrity and alignment with business and customer objectives; lead requirement analysis, low level architecture and component design, development, testing, integrations, and support.
Protect the integrity of the architecture and tech stack to enterprise standards; manage dependencies, code design, implementation, quality, data, and ongoing maintenance and operations; stay hands-on, continuously learn new approaches and frameworks; create technical specifications and review others’ code while mentoring teammates.
Develop lean, customer-centric solutions through rapid, low-cost experimentation; engage with customers and product teams before, during, and after delivery to ensure the right solution arrives at the right time.
Adopt an incremental delivery mindset that emphasizes action and evidence over extensive planning; deliver lean, maintainable, and supportable solutions.
Collaborate with cross-functional teams including product management, UX, and delivery; integrate diverse perspectives to balance feasibility, viability, usability, and value.
Demonstrate advanced technical proficiency in modern software engineering practices, including AI and agentic SSDLC, enabling daily product deployments with full automation from discovery to production and operations with quality checks throughout the lifecycle.
Acquire domain knowledge rapidly and translate business needs into technical specifications and code; contribute as a reliable, quality-focused team member.
Communicate complex technical concepts clearly and persuasively; influence teammates and product teams with evidence-based trade-offs and coherent narratives aligned to business goals.
Engage with product engineering teams at all levels and with customers as needed; foster co-creation and shared momentum toward achieving product goals.

Requirements

A bachelor's degree in computer science, software engineering, data science, machine learning, or a related discipline; experience remains a key factor.
6+ years of experience with most of the following: Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, and unit testing frameworks.
3+ years of experience building AI/ML applications, with hands-on GenAI experience across LLM integration (OpenAI, Anthropic, or open-source models), RAG pipelines, prompt engineering, and vector databases.
3+ years of cloud-native engineering experience, using FaaS, PaaS, or micro-services on Azure, AWS, or GCP, including their AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI.
1+ years of experience establishing engineering standards, including actively leading, mentoring, and guiding teammates in adopting and improving these standards.
Experience with Business Context Diagrams (BCD), sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, and code instrumentation, plus AI-augmented spec-driven development.
Familiarity with methodologies and tools such as XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow, and agentic AI frameworks (for example LangFuse, LangSmith, or similar multi-agent orchestration tools) to deliver high-quality products rapidly.

Technologies

Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Azure, AWS, GCP, LangFuse, LangSmith, MLflow, GitHub, ADO, SonarQube

Compensation

USD 118,700 - 243,700 per year

Benefits

Discretionary annual incentive program
Average travel allowance of up to 10 percent based on work and project needs
Limited immigration sponsorship may be available

The Team

US Deloitte Technology Product Engineering modernizes software and product delivery into a scalable model focused on value and outcomes. As Deloitte's primary internal development group, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations, supporting Deloitte’s ongoing success and growth.

The Successful Candidate Will Possess

Excellent interpersonal and organizational skills, with the ability to manage diverse situations, complex projects, and changing priorities, demonstrated with passion, empathy, and care.

Other

Travel up to 10 percent on average, depending on the work and products you build
Limited immigration sponsorship may be available

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Today

Principal Machine Learning Engineer, Accelerated Apache Spark

NVIDIA Santa Clara, CA

Santa Clara, CA

Today

$272k - $431k/yr Full time Python Big Data Bigdata

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Job Description

NVIDIA seeks a Principal Machine Learning Engineer to guide ML engineering on the GPU-accelerated Apache Spark program in Santa Clara, focusing on ML-driven performance prediction and optimization for Spark workloads. The role also involves building AI-based deployment tools and providing mentorship across environments. This onsite position offers a salary range of USD 272,000 to 431,250 per year.

Role overview

In this capacity, you will lead the ML engineering efforts for a GPU-accelerated Spark initiative, developing ML-based methods to forecast performance and optimize Spark workloads. You will additionally create AI-enabled tools and provide technical mentorship to enable deployment across diverse environments.

Responsibilities

Design and implement ML solutions for forecasting performance and optimizing GPU-accelerated enterprise Apache Spark workloads.
Develop advanced algorithms and adaptive systems to continually enhance Spark performance on GPUs.
Create AI-driven agents and tools to assist with diagnosing system issues and optimizing applications.
Collaborate with partners and customers to deploy complex ML solutions across varied environments.
Maintain deep domain expertise by staying current with the latest advances in ML systems and algorithms.
Provide technical leadership and mentorship in data science and ML for a team of engineers.

Requirements

Education: BS, MS, or PhD or equivalent experience in Machine Learning, Data Science, Computer Science, or a closely related field.
12+ years of professional experience designing, implementing, and productionizing high-quality ML/DL solutions.
5+ years of experience as a technical lead in ML model development.
Proven hands-on experience (2+ years) with large-scale data processing platforms such as Apache Spark.
Demonstrated ability to apply modern tooling and robust practices across all stages of building, deploying, and maintaining ML models.
Excellent programming skills in Python and related data science libraries (NumPy, pandas, scikit-learn, SciPy, PyTorch, TensorFlow).
Deep expertise in advanced ML methodologies, including LLMs/GenAI, reinforcement learning, and adaptive online ML systems.
Strong capability in feature engineering, feature importance assessment, and developing boosted tree models (e.g., XGBoost).

Technologies

Python
NumPy
pandas
scikit-learn
SciPy
PyTorch
TensorFlow
Apache Spark
XGBoost
Scala
Java
C++
CUDA

Benefits

Equity and benefits

Ways to stand out from the crowd

Understanding of the internal workings and architecture of Apache Spark
Familiarity with NVIDIA GPUs and CUDA
Experience coding in Scala, Java, and/or C++

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Today

Senior Machine Learning Engineer, End‑to‑End Autonomous Driving

NVIDIA Santa Clara, CA

Santa Clara, CA

Today

$184k - $357k/yr Full time Senior Active Learning Artificial Intelligence

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Job Description

NVIDIA in Santa Clara is seeking a Senior Machine Learning Engineer to design, train, and deploy end-to-end autonomous driving models while building data-centric pipelines and data flywheels that accelerate development. This onsite role involves close collaboration with researchers and engineers to convert advanced research into robust, production-ready ML systems for autonomous vehicles.

Responsibilities

Design, implement, and train scalable end-to-end driving models for autonomous vehicles.
Drive the data flywheel by identifying failure modes, defining data collection and labeling needs, and iterating models to close real-world performance gaps.
Build, curate, and maintain high-quality multimodal datasets including video, sensor streams, and language/action traces for end-to-end driving.
Develop and apply data-centric learning strategies such as active learning, curriculum learning, automated hard-example mining, outlier and novelty detection, and semi/self-supervised methods.
Explore and productize new data sources, including simulation, synthetic data, and world-model-based generation or augmentation to improve coverage and robustness.
Design and implement automated data workflows that handle discovery, labeling, evaluation, and retraining to maximize development velocity.
Foster collaborative partnerships with researchers and engineers to transform innovative research into robust, production-ready ML models.

Requirements

PhD with 4+ years, MS with 6+ years, or BS (or equivalent) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related field.
Strong background in modern deep learning, including transformer architectures, video modeling, and multimodal VLM/VLA or foundation models.
Hands-on experience training and deploying deep learning models on real-world datasets, covering preprocessing, distributed training, evaluation, debugging, and iterative improvement.
Practical experience with data-centric methods such as active learning, curriculum learning, outlier/novelty detection, or large-scale sample mining.
Proficiency in Python and at least one major deep learning framework (PyTorch, TensorFlow, or JAX), plus solid software engineering practices (testing, code reviews, CI/CD).
Demonstrated ability to collaborate across teams, drive designs from prototype to production, and communicate with technical and non-technical partners.
Track record of leading complex cross-team projects, setting technical direction, and making critical technical decisions that impact multiple teams or products.

Technologies

Python
PyTorch
TensorFlow
JAX

Benefits

Equity
Benefits

Ways to stand out from the crowd

Experience building and operating data flywheels or large-scale data pipelines for ML, including data quality monitoring and continuous retraining loops.
Direct experience with end-to-end driving models, large-scale behavior cloning, or reinforcement/imitation learning for driving or robotics.
Experience leveraging simulation, synthetic data, or world models to generate training and evaluation data for autonomous systems.
Contributions to advanced data-centric ML methods, VLM/VLA, or autonomous driving through publications, open-source projects, or widely used internal tools.
Background with safety, reliability, and validation requirements for autonomous driving or other safety-critical applications.

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Today

Senior Lead AI Engineer (FM Hosting)

Capital One McLean, VA

McLean, VA

Today

$230k - $262k/yr Full time Senior Artificial Intelligence Engineer

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Job Description

Capital One offers a path to build responsible, reliable AI systems that change banking for good. This onsite role in McLean, VA sits on the Intelligent Foundations and Experiences team and offers a competitive compensation package, including a salary range of USD 229,900 to 262,400 per year, comprehensive health and financial benefits, and performance-based incentives. You will work with a cross-functional group of engineers, research scientists, technical program managers, and product managers to deliver AI powered products that impact both colleagues and customers.

Responsibilities

Collaborate with a cross-functional team to deliver AI enabled products that transform how associates work and how customers interact with Capital One.
Design, develop, test, deploy, and support AI software components such as foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Utilize a broad stack of open source and SaaS AI technologies including AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
Invent and apply advanced LLM optimization techniques to boost scalability, cost efficiency, latency, and throughput in production AI systems.
Contribute to the technical vision and long-term roadmap of foundational AI systems at Capital One.

Requirements

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related field with at least 6 years of experience developing AI and ML algorithms or technologies; or a Master's degree in the same fields with at least 4 years of experience.
At least 6 years of experience programming with Python, Go, Scala, or Java.

Technologies

Python
Go
Scala
Java
AWS Ultraclusters
Huggingface
VectorDBs
Nemo Guardrails
PyTorch

Benefits

Health benefits
Financial benefits
Other benefits
Performance-based incentive compensation (cash bonuses and long-term incentives)

Team description

The Intelligent Foundations and Experiences (IFX) team sits at the center of Capital One's AI vision. We collaborate with partners across the company to advance the state of the art in AI engineering and to deploy proprietary solutions that deliver value to millions. Our models and platforms empower teams to enhance products with the power of AI, driving meaningful outcomes across the business.

The ideal candidate

Enjoys building systems, cares deeply about quality, and is committed to doing the right thing to drive impact in banking.
Keeps pace with the latest AI research and can translate publications into production-ready techniques when appropriate.
Adapts quickly, seeks clarity in large, complex problems, asks questions, and communicates findings concisely; comfortable sharing new ideas even when they are unproven.
Strong technical foundation in engineering and mathematics; able to spot optimization opportunities across hardware, software, and AI to improve performance.
Resilient trailblazer who can chart new paths to achieve business goals when the route is unclear.

Basic qualifications

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related field with at least 6 years of AI/ML experience, or Master's degree in the same fields with at least 4 years of AI/ML experience.
At least 6 years of experience programming with Python, Go, Scala, or Java.

Preferred qualifications

7 years of experience deploying scalable and responsible AI solutions on cloud platforms (AWS, Google Cloud, Azure, or equivalent private cloud).
Experience designing, developing, integrating, delivering, and supporting complex AI systems.
Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders.
Experience developing AI and ML algorithms or technologies (LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Go.
Experience optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
Strong interest in AI research and systems, with the ability to judiciously apply novel techniques in production.
Excellent communication and presentation skills, capable of articulating complex AI concepts to peers.

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Today

Lead AI Engineer (AI Foundations)

Capital One McLean, VA

McLean, VA

Today

$197k - $225k/yr Full time Ai Ml Artificial Intelligence Engineer

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Job Description

Capital One seeks a Lead AI Engineer focused on AI Foundations to design, build, deploy, and sustain AI software components, including foundation model training, LLM inference, similarity search, guardrails, evaluation, experimentation, governance, and observability. The role collaborates with cross-functional teams to shape the technical vision for foundational AI systems, leveraging Open Source and SaaS AI technologies. This onsite position is based in McLean, Virginia, with a salary range of USD 197,300 to 225,100 per year.

Summary

In this senior engineering role, you will lead efforts to design, develop, and support AI software components spanning foundation model training, large language model inference, similarity search, governance, evaluation, experimentation, and observability. You will contribute to Capital One's technical direction for foundational AI systems and work closely with engineers, researchers, program managers, and product managers to deliver AI powered products that impact both associates and customers.

Responsibilities

Collaborate with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI driven products that transform how associates work and how customers interact with Capital One.
Design, develop, test, deploy, and maintain AI software components including foundation model training, LLM inference, similarity search, guardrails, evaluation, experimentation, governance, and observability.
Utilize a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, VectorDBs, Nemo Guardrails, PyTorch, and others.
Create and apply advanced LLM optimization techniques to enhance production AI systems in terms of scalability, cost, latency, and throughput.
Contribute to the technical vision and the long term roadmap for foundational AI systems at Capital One.

Requirements

A master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields with at least 2 years of relevant AI/ML development experience, or a bachelor's degree in the same fields with at least 4 years of related experience.
At least four years of programming experience in Python, Go, Scala, or Java.

Technologies

AWS Ultraclusters
Hugging Face
VectorDBs
Nemo Guardrails
PyTorch

Benefits

Health, financial, and other benefits that support total well-being.
Performance-based incentive compensation, including cash bonuses and long-term incentives.

Overview

Capital One is dedicated to building responsible and reliable AI systems that advance banking for good. The company has long led in applying machine learning to deliver real-time, personalized customer experiences and continues to invest in technology infrastructure and top talent. This focus positions Capital One at the forefront of enterprise AI, enabling capabilities that range from explaining charges to answering customer questions in real time.

Team Description

The Intelligent Foundations and Experiences (IFX) team sits at the core of bringing Capital One's AI vision to life. We partner across the organization to push the boundaries of AI research and engineering, building and deploying proprietary solutions that drive value for millions of customers. Our AI models and platforms empower teams to enhance products with AI, delivering measurable impact across the business.

The Ideal Candidate

Enjoys building scalable systems and takes pride in delivering high-quality work that advances banking outcomes.
Maintains a strong interest in the latest AI research and can translate publications into production-ready approaches.
Adapts quickly to ill-defined problems, asks the right questions, and communicates findings clearly while proposing new ideas when appropriate.
Is deeply technical with a solid foundation in engineering and mathematics, leveraging hardware, software, and AI to uncover optimization opportunities.
Actively pursues a trailblazing path to achieve business goals when the route is uncertain.

Preferred Qualifications

Six or more years deploying scalable and responsible AI solutions on cloud platforms (AWS, Google Cloud, Azure, or equivalent private cloud).
Experience designing, developing, delivering, and supporting AI services.
Proven work on AI and ML algorithms or technologies (LLM inference, similarity search and vector databases, guardrails, memory) using Python, C++, C#, Java, or Go.
Experience optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
Strong interest in staying current with AI research and systems and applying novel techniques in production.

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Today

Sr. Lead AI Engineer (Gen AI Platform Services)

Capital One McLean, VA

McLean, VA

Today

$230k - $262k/yr Full time Senior AI Artificial Intelligence

Apply Now

Job Description

Capital One offers an onsite Sr. Lead AI Engineer position in McLean, VA with a competitive annual compensation range of USD 229,900 to 262,400. This role centers on designing, building, deploying, and supporting AI software components and foundational AI systems, leveraging Open Source and SaaS AI technologies to deliver AI powered products. The team emphasizes collaboration across engineers, research scientists, technical program managers, and product managers to create solutions that transform how associates work and how customers interact with Capital One. In addition to a comprehensive benefits package, the role provides performance-based incentives and opportunities for ongoing learning and growth.

Responsibilities

Collaborate with a cross-functional team to deliver AI-powered products that impact internal processes and customer experiences.
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Utilize a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
Invent and apply state-of-the-art LLM optimization techniques to improve performance metrics such as scalability, cost, latency, and throughput for production AI systems.
Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.

Requirements

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of AI/ML development experience, or a Master’s degree in similar fields plus at least 4 years of AI/ML development experience.
At least 6 years of experience programming with Python, Go, Scala, or Java.

Technologies

AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch
Programming: Python, Go, Scala, Java, Golang

Benefits

Health benefits covering medical, financial, and other protections.
Performance-based incentive compensation, including cash bonuses and long-term incentives.

Ideal candidate

Enjoys building systems and takes pride in delivering high-quality work while aligning with the goal of improving banking for good.
Keeps pace with the latest AI research and can translate scholarly insights into production-ready solutions.
Adapts quickly, brings clarity to complex problems, asks probing questions, and communicates findings concisely. Has the courage to propose new ideas, even if unproven.
Strong technical foundation in engineering and mathematics, with fluency across hardware, software, and AI to identify optimization opportunities others may miss.
Resilient and proactive, capable of forging new paths to achieve business goals when approaches are uncertain.

Preferred qualifications

About 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (AWS, Google Cloud, Azure, or equivalent private cloud).
Experience designing, developing, integrating, delivering, and supporting complex AI systems.
Proven ability to lead and mentor an engineering team and influence cross-functional stakeholders.
Experience developing AI and ML algorithms or technologies such as LLM inference, similarity search, vector databases, guardrails, memory, using Python, C++, C#, Java, or Golang.
Experience optimizing training and inference to improve hardware utilization, latency, throughput, and cost.
Passion for staying current with AI research and systems, applying novel techniques in production judiciously.
Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers.

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Today

Lead AI Engineer (AI Foundations, LLM Core and Agentic AI)

Capital One McLean, VA

McLean, VA

Today

$197k - $225k/yr Full time Agentic Ai Ai Ml Artificial Intelligence

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Job Description

Capital One seeks a Lead AI Engineer focusing on AI foundations, LLM core, and agentic AI, partnering with cross-functional teams to design and deploy AI powered products, including foundation model training and LLM inference, with emphasis on optimization and governance.

Responsibilities

Collaborate with engineers, research scientists, technical program managers, and product managers to deliver AI driven products that transform how associates work and how customers interact with Capital One.
Design, build, test, deploy, and sustain AI software components covering foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Utilize a broad mix of open source and SaaS AI tools including AWS Ultraclusters, Hugging Face, VectorDBs, Nemo Guardrails, and PyTorch among others.
Develop and apply cutting edge LLM optimization techniques to improve scalability, cost, latency, and throughput for large scale production AI systems.
Contribute to the technical vision and long term roadmap of foundational AI systems at Capital One.

Requirements

Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of AI/ML algorithm development experience, or a Master’s degree in the same disciplines plus at least 2 years of experience.
At least 4 years of experience programming with Python, Go, Scala, or Java.

Technologies

AWS Ultraclusters
Hugging Face
VectorDBs
Nemo Guardrails
PyTorch
Python
Go
Scala
Java

Benefits

Capital One provides a comprehensive, competitive, and inclusive benefits package spanning health, financial security, and additional well being supports.
The role is eligible for performance based incentive compensation, which may include cash bonuses and long term incentives. Incentives can be discretionary or non discretionary depending on the program.

Overview

Location: McLean, VA onsite. Salary: USD 197,300 - 225,100 per year. Capital One is building responsible and reliable AI systems to transform banking for the better, with a track record of using machine learning to deliver real time, personalized customer experiences. The company invests in technology infrastructure and talent to stay at the forefront of enterprise AI adoption.

Team Description

The Intelligent Foundations and Experiences (IFX) team sits at the center of Capital One's AI efforts. We partner with stakeholders across the organization to advance AI science and engineering, building and deploying proprietary solutions that drive business value for millions of customers. Our AI models and platforms empower teams to enhance products with the transformative power of AI.