United States

Data Jobs in United States

3,276 jobs found

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1mo ago

Machine Learning Engineer

Mariana Minerals Ann Arbor, MI

Ann Arbor, MI

1mo ago Closed

$120k - $180k/yr Full time Ai Ml Artificial Intelligence Engineer

This position is no longer accepting applications (closed Sep 9, 2026).

Job Description

Mariana Minerals is building machine learning systems that control mineral refining facilities, with a strong focus on reinforcing learning in physically realistic simulators and closing the gap to real plant data. This is an onsite role in Ann Arbor, MI, where your work moves from experimentation to production. The salary range is $120,000 - $180,000 per year.

What you’ll do

Run reinforcement learning experiments in physically realistic simulators of mineral processing operations, then translate results into improved controllers.
Build and refine training environment components, including reward functions, observations, and action logic, with guidance from senior engineers.
Train control models, track and interpret performance, and investigate why a model underperforms.
Close the loop between simulation and reality by comparing model behavior to real plant data and flagging where simulated physics diverge.
Write clean, well-tested code and contribute to the services that deploy models into production.
Partner with process and chemistry experts to understand the unit operations being modeled.

What you bring

2-8+ years of experience (including internships or research) in machine learning, reinforcement learning, or scientific computing, or a strong recent graduate with demonstrated project depth.
Solid grounding in machine learning fundamentals, with working knowledge of modern deep learning; reinforcement learning experience is a strong plus.
Proficiency in Python and comfort reading and debugging an existing codebase.
Curiosity about physical, industrial systems and willingness to learn chemistry and process engineering from experts who challenge assumptions.
A self-starter who asks good questions, ships, and escalates blockers early.

How the technology is used

The stack uses the same reinforcement learning toolkits that power self-driving vehicles and humanoid robots, adapted for autonomous, short-interval control of mineral refining circuits. Models adjust operating set points and configurations in real time, optimizing across lithium recovery, reagent consumption, energy intensity, and equipment uptime simultaneously. Training happens in physically realistic simulators of process units, then performance is validated against real plant data before anything is introduced to live equipment.

Why this matters (and why you’ll like it)

We own the projects, generate the data, and close the loop.
Each facility helps make the software smarter, and the next one faster and cheaper.
Mining is one of the last major industrial sectors that hasn’t been rebuilt with modern software.
Your work directly shapes how critical minerals are produced at scale in the coming decades.

Culture at Mariana Minerals

Extreme Ownership – take full responsibility for outcomes and drive toward solutions.
Engineer Out Requirements, then Automate – simplify, optimize, and automate for scale.
Share Your Legos – collaborate openly, share knowledge, and empower each other to build bigger, better solutions.

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1mo ago

Machine Learning Engineer

Speria Atlanta, GA

Atlanta, GA

1mo ago Closed

Full time Agentic Ai Ai Ml Artificial Intelligence

This position is no longer accepting applications (closed Sep 9, 2026).

Job Description

Speria MTech is hiring a Machine Learning Engineer in Atlanta, GA (hybrid) to build scalable ML and optimization systems for real-time decision-making.

Responsibilities

Design, develop, and maintain machine learning and optimization pipelines
Build production-grade models and deploy them into working systems
Create feature pipelines using distributed systems such as Spark
Partner with data engineering to ensure data readiness for modeling and deployment
Develop decisioning systems that support automated actions
Continuously monitor model performance and drive ongoing improvements

Requirements

Bachelor’s or Master’s degree in a relevant field (MS may qualify with 1–2 years; BS typically 4–6 years)
2–4 years of experience in Machine Learning or optimization
Experience deploying machine learning systems in production
Familiarity with an end-to-end ML flow, including Databricks and CI/CD
Strong Python skills at a production level
Experience with ML frameworks: PyTorch, TensorFlow, and/or scikit-learn

Technologies

Python, PyTorch, TensorFlow, scikit-learn
Spark, Databricks
CI/CD, SQL, Git
LLMs, generative AI, agent-based systems

Preferred Skills

Strong SQL and Apache Spark experience
Experience building feature engineering pipelines for machine learning
Hands-on Git experience, CI/CD, and reproducible workflows
Experience working on real-time systems
Familiarity with LLMs, generative AI, and agent-based systems
Degree experience note: MS may qualify with 1–2 years; BS typically 4–6 years

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1mo ago

Machine Learning Engineer

Ampacimon Belgium, WI

Belgium, WI

1mo ago Closed

Full time Artificial Intelligence Data Pipeline Machine Learning Engineer

This position is no longer accepting applications (closed Sep 9, 2026).

Job Description

Ampacimon is seeking a Machine Learning Engineer to build and maintain AI and machine learning solutions in production for its grid optimization products. The position focuses on designing domain-specific algorithms, improving model reliability, and ensuring ML training and serving pipelines support customer-facing and internal systems.

Role Summary

In this role, you will design and integrate AI/ML components that use sensor data alongside additional inputs such as remote sensors, weather providers, and customers’ own data. You will also provide technical support to customers and internal departments, and contribute to software development frameworks through sample algorithms and libraries.

Responsibilities

Design, implement, maintain, and optimize domain-specific AI/ML algorithms using sensor data and additional sources (remote sensors, weather providers, and customer data), and integrate these algorithms into Ampacimon’s software platforms
Own ML models in production by keeping them reliable at scale, improving accuracy, and automating the pipelines used to train and serve models
Support software development frameworks by providing sample algorithms and libraries
Deliver technical support to customers and internal departments

Requirements

MSc in Computer Science or Data Science (equivalent or higher)
Hands-on experience applying advanced machine learning algorithms and statistical methods, including regression, simulation, scenario analysis, modeling, clustering, decision trees, and neural networks
Experience querying databases, working with web services, and using statistical or computing languages
Experience automating ML model variations using automated scripts or CI pipelines
Experience with Python and SQL
Proven experience deploying and maintaining ML models in production
Strong experience in time series data processing
Strong written and verbal communication and presentation skills in English and French
Comfort working in an international environment with remote teams
Genuine appetite for learning new technologies and taking on varied tasks

Technologies

Python
SQL
CI pipelines

Nice to Have

Working experience in Java and ONNX models
Experience developing customer-facing applications
Experience working with GIS, 3D, or Lidar data
Experience with SCADA systems and energy-sector applications
Experience with unit testing

Work Location and Reporting

The role is based in Belgium, WI and is onsite. Reporting will be to the Lead of Software, supporting a software development team responsible for integration into customer-facing applications and internal systems.

How to Apply

To apply, fill in the form below or send your application to jobs@ampacimon.com.

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1mo ago

Machine Learning Engineer

Stellantis Auburn Hills, MI

Auburn Hills, MI

1mo ago Closed

Full time Big Data Data Analysis Data Analytics

This position is no longer accepting applications (closed Sep 9, 2026).

Job Description

Build statistical models and simulations that directly influence future Vehicle Order Guides (VOGs) at Stellantis. In this onsite role in Auburn Hills, MI, you will use a customer-level preference simulation approach to improve vehicle configuration optimization for upcoming model years.

What you will do

Design and run large-scale simulations, including scenarios such as 50,000 synthetic customers, to model vehicle purchase behavior. Your outputs will feed a customer-level preference simulation engine used to improve the optimization of Vehicle Order Guides (VOGs) for future model years.

Develop statistical and machine learning models using Databricks
Perform exploratory data analysis and feature engineering on complex datasets
Translate model results into optimized VOGs that support product configuration decisions
Collaborate closely with Data Engineering to refine and leverage curated datasets
Communicate insights and model recommendations to business stakeholders
Continuously evaluate and improve model accuracy and assumptions

You will work with datasets that may include:

Historical vehicle sales
Competitive sales data
Feature-level willingness-to-pay data
Customer preference models

What you bring

Bachelor’s Degree required
Minimum 5 years of experience in data science, machine learning, or applied statistics
Strong experience with Databricks (critical requirement)
Proficiency in Python including Pandas, NumPy, scikit-learn, and PySpark
Strong SQL skills
Solid foundation in statistical modeling, simulation techniques, and experimental design
Experience translating analytical results into business decisions

Additional focus areas (preferred)

Experience with choice modeling, conjoint analysis, or demand modeling
Background in automotive, pricing, or product optimization analytics
Experience working with large-scale simulation frameworks
Familiarity with Spark and distributed computing
Exposure to MLOps or model productionization

Technologies

Databricks, Python, Pandas, NumPy, scikit-learn, PySpark, SQL, Spark

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1mo ago

Machine Learning Engineer

Ventas, Inc. Chicago, IL

Chicago, IL

1mo ago Closed

$135k - $175k/yr Full time Ai Ml Artificial Intelligence Data Analysis

This position is no longer accepting applications (closed Sep 9, 2026).

Job Description

Ventas, Inc. is seeking a Machine Learning Engineer to design, build, deploy, and maintain production-grade machine learning solutions across the enterprise. This hybrid role in Chicago, IL focuses on scalable ML systems, model lifecycle management (MLOps), and integration with enterprise platforms.

Core Responsibilities

Design, develop, train, and deploy machine learning models using supervised and unsupervised methods such as regression, classification, clustering, and anomaly detection.
Build and maintain end-to-end ML pipelines, covering data ingestion, feature engineering, training, evaluation, and inference.
Collaborate with Data Science, Data Engineering, and business stakeholders to translate requirements into scalable technical solutions.
Apply MLOps best practices, including CI/CD, model versioning, monitoring, and retraining strategies.
Improve model performance, scalability, reliability, and cost efficiency for production deployments.
Integrate machine learning models into enterprise applications, APIs, and data platforms.
Support data quality efforts and contribute to model explainability while adhering to security, governance, and compliance standards.
Explain machine learning concepts and outcomes clearly to both technical and non-technical stakeholders.

Required Qualifications

Bachelor’s degree in Computer Science, Data Science, Engineering, or equivalent experience.
5+ years of experience building and deploying machine learning models in production environments.
Must be located in the Chicago, IL surrounding area or willing to relocate for the duration of employment.
Ability to work in a blended work environment with 3 days in office, transitioning between remote and in-office operations.
Proficiency in Python and experience with machine learning frameworks including TensorFlow, PyTorch, and Scikit-learn.
Strong experience using AWS SageMaker for data preparation, pipelines, and model deployment.
Experience with Git and modern software engineering best practices.
Familiarity with SQL, including T-SQL, and experience working with relational and geospatial databases.
Experience with retrieval-augmented generation or generative AI solutions is a plus.
Understanding of Agile development practices and comfort working in evolving, ambiguous environments.
Must be legally authorized to work in the United States without need for employer sponsorship now or in the future.

Technologies

Python
TensorFlow
PyTorch
Scikit-learn
AWS SageMaker
Git
SQL
T-SQL

Compensation & Location

Location: Chicago, IL (hybrid). Compensation: USD 135,000 to 175,000 per year.

Benefits

Discretionary incentive compensation
Comprehensive benefits package
Medical
Dental
Vision
Retirement savings
Paid time off
Other wellness benefits under applicable plan terms

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1mo ago

Machine Learning Engineer

Vuegen Hoffman Estates, IL

Hoffman Estates, IL

1mo ago Closed

$131k - $132k/yr Full time Ai Ml Artificial Intelligence Cloud

This position is no longer accepting applications (closed Sep 9, 2026).

Job Description

Join a Machine Learning Engineer team at Vuegen in Hoffman Estates, IL with an onsite focus on developing and deploying image-based ML models.

Key Responsibilities

Assist in developing and implementing machine learning models for image-based solutions within established guidelines.
Assist in researching and benchmarking state-of-the-art machine learning techniques by building proof-of-concept implementations, evaluating performance, and documenting results clearly.
Assist in deploying machine learning models on Google Cloud Platform (GCP) to meet scalability, performance, and reliability needs under the direction of the team lead.
Perform data collection, validation, and basic analysis to support model performance monitoring and ongoing improvement.
Collaborate with cross-functional teams to gather requirements and support implementation of technical solutions.
Stay current on emerging AI and Machine Learning technologies and apply relevant concepts to assigned project tasks.

Requirements

Master’s degree in CS, IT, Engg or related.
Salary range: USD 130,707 - 132,000 per year.
Send resume to hr@vuegen.com including the JOB ID.
Travel and relocation to various unanticipated client locations throughout the United States may be required.
Equal Opportunity Employer.

Technology Focus

Google Cloud Platform (GCP)

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1mo ago

Lead Data Engineer

Lutron Electronics Co., Inc Coopersburg, PA

Coopersburg, PA

1mo ago Closed

Full time Manager 3d Design Tools Amazon Eks

This position is no longer accepting applications (closed Sep 9, 2026).

Job Description

Lead the engineering efforts that power a modern, cloud-native data and AI platform for enterprise analytics.

Responsibilities

Shape and guide development of Lutron’s cloud-based data ecosystem.
Mentor data engineers, software engineers, and data scientists.
Set and drive data engineering best practices across governance, security, and scalability.
Improve data access and promote data literacy across the organization.
Process, clean, and validate the integrity of large-scale datasets.
Architect cloud-based solutions using AWS and Microsoft platforms.
Build business-ready data models to support analytics, KPIs, and decision-making across functional areas.
Develop and maintain ML and advanced analytics infrastructure to host, manage, and automate models.
Support AI/ML workflows by building scalable pipelines for model training, deployment, monitoring, and versioning.
Integrate AI-driven capabilities such as recommendation engines, natural language processing, and predictive analytics.
Optimize pipelines for large-scale feature engineering, experiment tracking, and real-time inference.
Partner with data scientists to productionize AI models and agents, with attention to performance, reliability, and compliance.
Ensure performance and data quality through SQL programming and optimization.
Explain technical concepts clearly to technical and non-technical stakeholders.
Provide automated analytics, dashboards, and data visualizations for business decisions.

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Science, Computer Engineering, or Software Engineering.
Minimum, cumulative GPA of 3.00 for all degrees earned.
8+ years of experience in a related field.
Proven expertise in modern data modeling, real-time and batch processing, and cloud-based architectures.