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Python Ml Developer Jobs in Indiana (NOW HIRING)

Working knowledge of Python, ML frameworks (PyTorch, TensorFlow, scikit-learn), and model evaluation--enough to partner effectively with data scientists * Feature Engineering Infrastructure:

Working knowledge of Python, ML frameworks (PyTorch, TensorFlow, scikit-learn), and model evaluation-enough to partner effectively with data scientists * Feature Engineering Infrastructure:

Working knowledge of Python, ML frameworks (PyTorch, TensorFlow, scikit-learn), and model evaluation-enough to partner effectively with data scientists * Feature Engineering Infrastructure:

AI/ML engineer

Indianapolis, IN · On-site

$100K - $120K/yr

Required : • Strong proficiency in Python and ML frameworks (PyTorch| TensorFlow| scikit-learn) • Experience with LLMs| prompt engineering| and generative AI platforms • Hands-on knowledge of ...

Senior AI/ML Engineer

Indianapolis, IN · On-site +1

$99K - $137K/yr

We own a modern full-stack architecture including TypeScript/React, Python, GraphQL, Golang , and ... We partner closely across AI/ML engineers , Product Operations , Product Management , Data Science ...

Senior AI/ML Engineer

Indianapolis, IN

$99K - $137K/yr

Overview: AI/ML Engineer: 10+ Years of Experience Skills AI/ML Strong Python Coding Experience LLM workflows (AWS/GCP/Azure) ETL workflows using Spark, Glue, Airflow, • Design, develop, and ...

Our company is seeking a detail-oriented and highly analytical ML Engineer who will assist in ... Strong expertise in data analysis tools and languages (e.g., Python, R, SQL). * Experience with ...

Our company is seeking a detail-oriented and highly analytical ML Engineer who will assist in ... Strong expertise in data analysis tools and languages (e.g., Python, R, SQL). * Experience with ...

Senior AI/ML Engineer

Indianapolis, IN

$99K - $137K/yr

AI/ML Engineer: • Design, develop, and maintain scalable Python applications, libraries, and scripts for data pipelines, APIs, and LLM workflows, ensuring code quality and reusability. • Craft ...

Build scalable AI applications using Python and FastAPI. * Design and maintain RESTful APIs for AI ... CI/CD pipelines and DevOps automation. * Multi-agent AI architectures. * Knowledge graph ...

Senior ML Engineer

Indianapolis, IN

$99K - $137K/yr

Collaborate with cross-functional teams (clinical engineering, finance, IT) to translate insights ... Proficiency in Python, SQL, and ML frameworks (Scikit-Learn, XGBoost, TensorFlow). * Excellent ...

Comscore, Total Visits, March 2025) Day to Day As a Software Engineer IV (ML) on the Machine ... Expertise in Python and modern ML frameworks like PyTorch & Triton. * Experience with AWS SageMaker ...

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Python Ml Developer information

What does a Python ML Developer do?

A Python ML Developer designs, builds, and deploys machine learning models using the Python programming language. They work with large datasets, clean and process data, select appropriate algorithms, and use libraries like TensorFlow, PyTorch, or scikit-learn to implement solutions. Their work often involves collaborating with data scientists and engineers to integrate machine learning models into applications. Additionally, they may be responsible for testing, tuning, and optimizing models to achieve the best possible performance in real-world scenarios.

What are some common challenges Python ML Developers face when deploying machine learning models to production?

Python ML Developers often encounter challenges such as ensuring model scalability, managing dependencies, and maintaining reproducibility when deploying models into production environments. Integrating machine learning models with existing systems can require close collaboration with DevOps and software engineering teams to streamline workflows and automate deployment pipelines. Additionally, monitoring model performance over time and handling data drift are crucial responsibilities to ensure continued accuracy and reliability of deployed solutions.

What are the key skills and qualifications needed to thrive as a Python ML Developer, and why are they important?

To thrive as a Python ML Developer, you need strong programming skills in Python, a solid understanding of machine learning algorithms, and a background in mathematics or statistics, often supported by a degree in computer science, engineering, or a related field. Familiarity with tools and libraries such as TensorFlow, scikit-learn, PyTorch, and version control systems like Git is essential, along with experience using data visualization and cloud platforms. Critical soft skills include problem-solving, adaptability, and effective communication to collaborate with cross-functional teams and explain complex models to stakeholders. These skills ensure the successful development, deployment, and maintenance of machine learning solutions that drive business value.

What is the difference between Python Ml Developer vs Data Scientist?

AspectPython Ml DeveloperData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; Python, ML certificationsBachelor's/Master's in Data Science, Statistics, or related; Python, ML certifications
Work EnvironmentSoftware development teams, AI/ML projectsResearch, data analysis, modeling teams
Employer & Industry UsageTech companies, startups, AI firmsFinance, healthcare, tech, research institutions
Common Search & ComparisonYesYes

Python ML Developers focus on building and deploying machine learning models using Python, often working closely with software engineering teams. Data Scientists analyze data, create models, and generate insights, often using Python along with statistical tools. While both roles require Python and ML knowledge, Python ML Developers are more involved in implementation and deployment, whereas Data Scientists focus on data analysis and research.

What job categories do people searching Python Ml Developer jobs in Indiana look for? The top searched job categories for Python Ml Developer jobs in Indiana are:
What cities in Indiana are hiring for Python Ml Developer jobs? Cities in Indiana with the most Python Ml Developer job openings:
Infographic showing various Python Ml Developer job openings in Indiana as of June 2026, with employment types broken down into 92% Full Time, 5% Part Time, and 3% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution.
Staff ML Engineer

Other

Medical, Dental, Vision, Life, Retirement

Posted 7 days ago


Group1001 rating

9.5

Company rating: 9.5 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

9th of 261 rated insurance


Job description

Staff ML Engineer

We're building AI&ML-powered products that will transform how Group 1001 approaches pricing optimization, claims automation, and risk intelligence. To do this at scale, we need robust ML infrastructure—not just great models.

As a Staff ML Engineer, you'll focus on the MLOps and infrastructure layer that makes ML production-ready: model serving, feature pipelines, experiment tracking, and CI/CD for ML. You'll help shape our ML platform architecture, working alongside Platform Engineering teams to ensure ML workloads run reliably on our modern stack: Snowflake, Dagster, Coalesce, Palantir and AWS SageMaker.

This role is for engineers who are as passionate about infrastructure, deployment, and operationalizing ML as they are about the models themselves

How You'll Contribute:

  • Partner with Data & Platform Engineering to define how ML workloads integrate with our Snowflake-Dagster-Palantir ecosystem
  • Evaluate and recommend tooling for the ML stack—balancing build vs. buy decisions against our scale and compliance needs
  • Contribute to platform roadmap discussions, advocating for infrastructure investments that accelerate ML delivery
  • Establish CI/CD pipelines for ML: automated testing, model validation, staged deployments, and rollback capabilities using SageMaker Pipelines, Step Functions, or similar orchestration
  • Implement model monitoring and observability: drift detection, performance degradation alerts, and automated retraining triggers
  • Architect ML workloads on AWS: SageMaker (Training Jobs, Processing, Endpoints), EC2/EKS for custom serving, S3 for artifact storage, and IAM for secure access patterns
  • Optimize for cost and performance—right-sizing instances, spot instance strategies, auto-scaling endpoints, and efficient GPU utilization
  • Integrate ML infrastructure with our Dagster orchestration layer for end-to-end pipeline visibility
  • Mentor senior ML engineers and technical leads, developing the next generation of ML engineering leadership

What We're Looking For:

Technical Skills:

  • MLOps & Model Serving: Hands-on experience with model serving frameworks (SageMaker Endpoints, Seldon Core, BentoML, Ray Serve, or TensorFlow Serving); building and operating inference infrastructure at scale
  • CI/CD for ML: Building ML pipelines with SageMaker Pipelines, Kubeflow, Airflow, or Dagster; automated model testing, validation gates, and deployment automation
  • AWS & Cloud Infrastructure: Strong AWS experience—SageMaker, EKS/ECS, Lambda, Step Functions, S3, IAM; infrastructure-as-code (Terraform, CDK, CloudFormation)
  • Monitoring & Observability: Model monitoring, drift detection, alerting; tools like Evidently, WhyLabs, SageMaker Model Monitor, or custom solutions
  • Core ML Fundamentals: Working knowledge of Python, ML frameworks (PyTorch, TensorFlow, scikit-learn), and model evaluation—enough to partner effectively with data scientists
  • Feature Engineering Infrastructure: Experience with feature stores (SageMaker Feature Store, Feast, Tecton, or similar); designing feature pipelines for both batch and real-time serving
  • Experiment Tracking & Registry: MLflow, Weights & Biases, SageMaker Experiments, or similar; establishing reproducibility and governance across ML projects
  • Nice to Have: Palantir Foundry, Kubernetes, Bedrock, cost optimization strategies for ML workloads

Education:

  • Bachelor's degree in Computer Science, Data Science, Engineering, or related field
  • Master's degree or equivalent experience preferred

Experience:

  • 6-10 years in ML engineering, MLOps, or platform engineering with a focus on productionizing ML systems
  • Demonstrated experience building ML infrastructure that others build upon—serving layers, feature stores, or MLOps tooling
  • Track record of improving ML delivery velocity through infrastructure and automation
  • Proven ability to work cross-functionally with data scientists, platform engineers, and stakeholders
  • Experience mentoring and developing senior engineers and technical leaders
  • Strong executive presence with ability to influence stakeholders at all levels of the organization

Preferred Qualifications:

  • Experience in insurance or financial services with deep understanding of industry challenges
  • Recognized expertise through conference presentations, publications, or industry speaking engagements
  • Experience with enterprise-scale systems and complex technical environments
  • Proven ability to build consensus and drive alignment across multiple teams and stakeholders

Competencies and Soft Skills:

  • Executive presence with ability to influence senior leadership and drive organizational change
  • Strategic vision with ability to define long-term technical direction aligned with business goals
  • Strong leadership skills with proven ability to develop and mentor senior technical talent
  • Exceptional communication skills with ability to articulate technical strategy to executive audiences
  • Political acumen with ability to navigate complex organizational dynamics and build consensus

Compensation: Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay for this position ranges from $190,000/year in our lowest geographic market up to $215,000/year in our highest geographic market. Pay is based on factors such as market location, job-related skills, and experience.

Benefits Highlights:

Employees who meet benefit eligibility guidelines and work 30 hours or more weekly, have the ability to enroll in Group 1001's benefits package. Employees (and their families) are eligible to participate in the Company's comprehensive health, dental, and vision insurance plan options. Employees are also eligible for Basic and Supplemental Life Insurance, Short and Long-Term Disability. All employees (regardless of hours worked) have immediate access to the Company's Employee Assistance Program and wellness programs—no enrollment is required. Employees may also participate in the Company's 401K plan, with matching contributions by the Company.

Group 1001, and its affiliated companies, is strongly committed to providing a supportive work environment where employee differences are valued. Diversity is an essential ingredient in making Group 1001 a welcoming place to work and is fundamental in building a high-performance team. Diversity embodies all the differences that make us unique individuals. All employees share the responsibility for maintaining a workplace culture of dignity, respect, understanding and appreciation of individual and group differences.