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4 jobs found

Today

Senior Data Analyst

SN Cloud Solutions Chicago, IL

Chicago, IL

Today

Full time Python Senior AWS

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Job Description

SN Cloud Solutions is hiring a Senior Data Analyst to support analytics and reporting through modern data platforms and reliable data pipelines. This hybrid role in Chicago, IL (60619) focuses on working with large datasets, ETL/ELT workflows, and distributed processing, with a strong emphasis on Python and PySpark.

With 10+ years of experience, you will help translate business and technical needs into data solutions while collaborating across data engineering and analytics stakeholders. The role also includes troubleshooting pipelines, improving performance and scalability, and documenting data flows and transformation logic.

What you’ll do

Understand business and technical data requirements and translate them into practical data solutions.
Partner with teams working across databases, data lakes, and modern data fabric architectures.
Develop, maintain, and troubleshoot ETL/ELT data pipelines.
Work with structured and semi-structured data from multiple sources.
Use Python and PySpark to support data processing, transformation, and analysis.
Conduct data cleansing, transformation, validation, and data quality checks.
Optimize data processing jobs and pipelines for performance and scalability.
Collaborate with data engineers, analysts, and business stakeholders to deliver usable outputs.
Support data integration and migration activities.
Document data flows, transformation logic, and technical processes.

What you bring

Strong understanding of data analytics and data concepts.
10+ years of experience in data analytics, data engineering, data integration, or related data technologies.
Understanding of databases, data lakes, and data fabric.
Hands-on or strong conceptual knowledge of ETL/ELT processes and tools/packages.
Good knowledge of Python.
Good understanding of Apache PySpark and distributed data processing.
Understanding of data transformation, data quality, and data integration.
Strong SQL and database fundamentals.
Good analytical and problem-solving skills.

Technology areas you’ll work with

Python, PySpark (Apache PySpark)
ETL, ELT
SQL
Databricks
Azure Data Factory, Azure
Snowflake, Microsoft Fabric
AWS, GCP

Preferred qualifications

Experience with cloud data platforms such as Azure, AWS, or GCP.
Knowledge of modern data warehouse/lakehouse architectures.
Experience with tools such as Databricks, Azure Data Factory, Snowflake, Microsoft Fabric, or similar platforms.
Understanding of data governance and data quality concepts.
Experience working in Agile environments.

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8d ago

AI Engineer

Transformativ, LLC Dallas-Fort Worth, TX

Dallas-Fort Worth, TX

8d ago

$75 - $100/hr Contract Agentic Ai Ai Engineer Artificial Intelligence

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Job Description

Transformativ, LLC builds production-ready enterprise AI solutions, and this AI Engineer role focuses on Agentic AI, LLMs, and multi-agent systems that automate real business processes. You will collaborate closely with executives and enterprise clients to turn operational challenges into practical, deployed AI applications in a flexible, hybrid consulting environment.

What you’ll do

Design and deploy production-ready Agentic AI and multi-agent systems for enterprise use cases.
Build enterprise AI applications using Python and LLM platforms such as OpenAI, Anthropic, Google Gemini, Azure OpenAI, or similar providers.
Develop AI workflows with orchestration frameworks including LangGraph, CrewAI, AutoGen, MCP, or comparable tooling.
Integrate AI solutions with APIs, databases, Microsoft 365, ERP, CRM, and other enterprise systems.
Partner with business leaders to translate operational challenges into AI solutions.
Lead technical design discussions and mentor other engineers when appropriate.
Evaluate emerging AI technologies and recommend practical approaches for delivery and adoption.

What you bring

Professional experience building production AI applications.
Strong Python development skills.
Hands-on experience with LLM APIs (OpenAI, Anthropic, Gemini, Azure OpenAI, and similar).
Experience with Agentic AI, autonomous agents, multi-agent systems, or AI orchestration frameworks.
Experience integrating REST APIs, databases, and enterprise applications.
Excellent communication and client-facing consulting skills.
Ability to explain complex AI concepts to both technical and business audiences.

Tools you may use

Python, OpenAI, Anthropic, Google Gemini, Azure OpenAI, LangGraph, CrewAI, AutoGen, MCP, Microsoft 365, ERP, CRM, REST APIs, databases, Semantic Kernel, AWS, Google Cloud, Azure, Machine Learning, Intelligent Automation, autonomous multi-agent systems.

Location and contract details

Location: Dallas-Fort Worth, TX (hybrid). Work location noted as McKinney, TX 75070; Dallas, TX is preferred. Remote may be considered for exceptional candidates.
Job type: 1099 Independent Contractor with Contract-to-Hire Opportunity.
Compensation: Competitive hourly rate based on experience, with pay listed as $75.00 to $100.00 per hour.

Why join Transformativ?

Work on cutting-edge enterprise AI implementations.
Help shape AI-powered business transformation through practical delivery.
Collaborate directly with executives and enterprise clients.
Long-term leadership and growth opportunities.
Flexible, high-impact consulting environment.

Additional preferred experience includes LangGraph, CrewAI, AutoGen, MCP, Semantic Kernel or similar frameworks; cloud platforms (Azure, AWS, Google Cloud); experience in healthcare, manufacturing, supply chain, finance, procurement, or private equity; and AI governance, security, evaluation, and responsible AI practices. Technical leadership or consulting experience is also valued.

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11d ago

AI & Machine Learning Engineer

OneBlood Saint Petersburg, FL

Saint Petersburg, FL

11d ago

Full time Agentic Ai Systems Ai Ml Artificial Intelligence

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Job Description

OneBlood is building AI and Machine Learning solutions that support business insights and help optimize operations across the organization. In this onsite role in Saint Petersburg, FL, you will oversee the end-to-end delivery of AI/ML projects, from pipeline development and model execution to deployment and ongoing improvements, partnering with cross-functional teams to bring reliable, evaluated solutions into real operational environments.

What you’ll do

Design, build, and maintain robust data pipelines to collect, clean, and transform data from multiple sources for analysis, modeling, and deployed operational workflows.
Develop and implement machine learning models across the full life cycle, including problem framing, data collection and preparation, feature engineering, model selection, training, evaluation, deployment, retraining, and continued advancement.
Design and build AI agents that execute within enterprise workflows across systems such as databases, CRMs, ticketing, and knowledge bases, ensuring deployments include reliable and safety guardrails.
Implement end-to-end agent orchestration, including prompting, memory/state, tool-calling, and retries/fallbacks, along with evaluation frameworks such as test suites, simulations, and human-in-the-loop review to improve accuracy and reduce errors.
Build and maintain Retrieval-Augmented Generation (RAG) GPT applications by integrating enterprise knowledge sources (documents and databases) using embeddings, vector search, and prompt orchestration, with evaluation and safety guardrails for grounded responses.
Analyze large datasets to identify trends, patterns, and insights, and create visualizations and reports to communicate findings to stakeholders.
Monitor and evaluate performance of data models and systems, making adjustments to optimize both accuracy and efficiency.
Document processes, methodologies, and model development to ensure transparency and reproducibility.
Provide training and support to other team members or departments on data tools, techniques, and best practices.
Consult with internal IT teams to help ensure infrastructure supports stable, well-designed, highly available, and well-maintained Data Science and AI applications.
Stay current with emerging technologies and industry trends to continuously improve data engineering practices and contribute to cutting-edge solutions.
Ensure data accuracy, consistency, and security by implementing and enforcing data governance policies and best practices.

What you bring

Bachelor’s degree in Computer Science, Analytics, or a related field from an accredited college or university; Master of Science preferred.
5+ years of experience in data engineering, data science, or a related role, including hands-on experience building and deploying machine learning models.
Advanced proficiency in Python and ML/data libraries including scikit-learn, TensorFlow, Keras, PyTorch, Pandas, and NumPy.
Strong knowledge of machine learning methods, including supervised learning (regression, classification) and unsupervised learning (clustering, dimensionality reduction, anomaly detection).
Strong SQL skills, including designing and querying relational databases and supporting data warehousing; familiarity with ETL/ELT workflows and tools such as SSIS or equivalents.
Working knowledge of medallion architectures.
Experience with cloud-based ML development and deployment on AWS, Azure, or Google Cloud.
Proficiency with version control and collaboration workflows, including Git, branching strategies, code review, and basic CI/CD concepts.
Expertise in probability and statistics, including experimental design, hypothesis testing, modeling uncertainty, performance measurement, and choosing appropriate evaluation metrics.
Experience building AI model-powered applications and workflows using model APIs, including prompt design, tool/function calling, structured outputs (JSON), and response validation/guardrails.
Strong understanding of RAG architectures, including document ingestion, chunking strategies, metadata design, embedding generation, and retrieval methods.
Hands-on experience with vector databases/search systems and tuning retrieval for relevance, latency, and cost.

Key technologies

Artificial Intelligence (AI), Machine Learning (ML)
Python, scikit-learn, TensorFlow, Keras, PyTorch
Pandas, NumPy, SQL
ETL, ELT, SSIS
AWS, Azure, Google Cloud
Git, CI/CD, JSON
RAG, vector databases/search systems, embeddings, vector search
Model APIs

Physical & environmental requirements

Work may involve periodic moderately physically demanding tasks, including lifting, carrying, pushing, and pulling of moderately heavy objects and materials up to 25 pounds. Assistance and proper techniques/equipment are required for moving heavier items.
Tasks may include climbing, stooping, kneeling, crouching, or crawling. Must be able to safely operate assigned vehicles, possibly for long distances.
Work occurs inside and/or outside with potential exposure to inclement weather, atmospheric elements, and pathogenic substances. Noise level is usually moderate.

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11d ago

Lead AI Engineer

Capital One New York, NY

New York, NY

11d ago

$215k - $246k/yr Full time Manager AI Ai Guardrails

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Job Description

As a Lead AI Engineer on Capital One’s Intelligent Foundations and Experiences (IFX) team, you will help build and deploy responsible, scalable AI systems and foundational AI capabilities. The role emphasizes AI software components and production LLM optimization to improve performance across key operating metrics.

Role Overview

The IFX team brings the company’s AI vision to life by advancing state-of-the-art science and AI engineering. In this role, you will contribute to technical foundations that enable teams across Capital One to enhance products using AI in responsible and scalable ways, delivering high-leverage impact to millions of customers.

Key Responsibilities

Collaborate with cross-functional partners including engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that improve 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.
Apply a broad stack of Open Source and SaaS AI technologies, including AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch, along with cloud platforms such as AWS, Google Cloud, and Azure.
Develop and introduce state-of-the-art 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 for foundational AI systems at Capital One.

Required Qualifications

Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master’s degree in a related field plus at least 2 years of experience developing AI and ML algorithms or technologies.
At least 4 years of experience programming with Python, Go, Scala, or Java.

Preferred Qualifications

6 years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
Experience designing, developing, delivering, and supporting AI services.
Experience developing AI and ML algorithms or technologies such as LLM inference, similarity search and VectorDBs, guardrails, and memory using Python, C++, C#, Java, or Golang.
Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
Passion for staying current with AI research and AI systems, and applying novel techniques judiciously in production.

Technology Stack

AWS Ultraclusters
Huggingface
VectorDBs
Nemo Guardrails
PyTorch
AWS, Google Cloud, Azure
Programming: Python, Go, Scala, Java, C++, C#, Golang
LLM and AI capabilities: Large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, observability, foundation model training, LLM optimization, memory

Compensation and Benefits

Salary range: USD 215,200 to 245,600 per year.
Incentive compensation: Performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI).
Benefits: A comprehensive, competitive, and inclusive set of health, financial, and other benefits to support overall well-being.

Team and Work Style

Work hand-in-hand with internal partners to advance AI engineering and science.
Build and deploy proprietary solutions central to the business, with value for millions of customers.
Focus on responsible and scalable deployment of AI models and platforms across Capital One.

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