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Ml Engineer Jobs in Indiana (NOW HIRING)

Group1001

Staff ML Engineer

Zionsville, IN · On-site

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 ...

Group1001

Staff ML Engineer

Zionsville, IN · On-site

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 ...

Keystone Cooperative

ML Engineer

Indianapolis, IN · On-site

Keystone Cooperative is seeking a detail-oriented and highly analytical ML Engineer to assist in driving AI-driven product development initiatives. The successful candidate will apply AI and ML ...

eTeam

AI/ML engineer

Indianapolis, IN · On-site

$100K - $120K/yr

Job Summary : eTeam is a company focused on AI and machine learning solutions, and they are seeking an AI/ML Engineer to lead technical initiatives. The role involves designing and optimizing machine ...

Keystone

ML Engineer

Indianapolis, IN · On-site

Our company is seeking a detail-oriented and highly analytical ML Engineer who will assist in driving our AI-driven product development initiatives. The successful candidate will possess a strong ...

Keystone Cooperative

ML Engineer

Indianapolis, IN · On-site

Our company is seeking a detail-oriented and highly analytical ML Engineer who will assist in driving our AI-driven product development initiatives. The successful candidate will possess a strong ...

Keystone Cooperative

ML Engineer

Indianapolis, IN · On-site

Keystone Cooperative is seeking a detail-oriented and highly analytical ML Engineer to assist in driving their AI-driven product development initiatives. The successful candidate will apply AI and ML ...

Vergence

Senior AI/ML Engineer

Bedford, IN · On-site

$93K - $128K/yr

Partner with project managers and engineering teams to define objectives for AI/ML systems in support of maneuver, surveillance, and engagement missions. * Develop and prototype AI/ML systems to ...

Jj

Staff AI/ML Software Engr, Navigation

Warsaw, IN

As a Staff AI/ML Software Engineer in the Navigation R&D team, you will architect, plan and lead the AI/ML development and integration for nextgeneration surgical navigation and planning systems. You ...

Pwc

ERP AI Engineer - Manager

Indianapolis, IN · On-site

$99K - $232K/yr

As a Manager, you will lead teams of data scientists and ML engineers, manage client relationships, and translate complex business challenges into AI-driven strategies and solutions. This role offers ...

Onebridge

AI/ML Technical Lead

Indianapolis, IN · On-site

... engineering and analytics. • Prepare executive-level reports and presentations, articulating ... ML/AI frameworks (e.g., TensorFlow, PyTorch, MLflow) and familiarity with Databricks ecosystem ...

Bespoke Labs

Machine Learning Engineer

Fort Wayne, IN · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Gary, IN · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Hammond, IN

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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Ml Engineer information

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$31.4K

$84.9K

$135.1K

How much do ml engineer jobs pay per year?

As of Aug 5, 2026, the average yearly pay for ml engineer in Indiana is $84,863.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,300.00 and $103,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an ML engineer?

To thrive as an ML Engineer, you need a solid background in mathematics, statistics, computer science, and experience with machine learning algorithms, often supported by a degree in a related field. Familiarity with programming languages like Python or R, ML frameworks such as TensorFlow or PyTorch, and data processing tools is typically required, with relevant certifications being a plus. Strong problem-solving, critical thinking, and communication skills help you translate complex data insights into actionable solutions and work effectively in teams. These abilities ensure accurate model development, effective deployment, and successful collaboration on data-driven projects.

Are machine learning engineers still in demand?

Machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. They typically require skills in programming, data analysis, and frameworks like TensorFlow or PyTorch, and often find opportunities in tech, finance, healthcare, and other sectors investing in AI solutions.

What is an ML engineer?

ML Engineers, or Machine Learning Engineers, are professionals who design, build, and deploy machine learning models into production systems. They bridge the gap between data science and software engineering, ensuring that machine learning solutions are scalable, reliable, and efficient. ML Engineers work with large datasets, develop algorithms, and optimize models for performance. They also collaborate with data scientists, software developers, and business stakeholders to solve real-world problems using artificial intelligence.

What is the difference between Ml Engineer vs Data Scientist?

AspectML EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related fields; knowledge of ML frameworksBachelor's or Master's in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentDevelops, deploys, and maintains ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, startups, and enterprises deploying ML solutionsResearch institutions, tech firms, and industries relying on data analysis

While both roles involve working with data and machine learning, ML Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights to inform business decisions. The roles often overlap but differ in their core responsibilities and focus areas.

What are some common challenges ML engineers face when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring models remain accurate over time as data changes (known as data drift), optimizing models for speed and scalability, and integrating models seamlessly with existing software systems. Additionally, maintaining model performance in real-world environments can require continuous monitoring, retraining, and close collaboration with data engineers and DevOps teams. Addressing these challenges typically involves robust testing, using automated pipelines, and staying up-to-date with the latest MLOps best practices.
What are the most commonly searched types of Ml Engineer jobs in Indiana? The most popular types of Ml Engineer jobs in Indiana are:
What are popular job titles related to Ml Engineer jobs in Indiana? For Ml Engineer jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Ml Engineer jobs in Indiana look for? The top searched job categories for Ml Engineer jobs in Indiana are:
What cities in Indiana are hiring for Ml Engineer jobs? Cities in Indiana with the most Ml Engineer job openings:
Ml Engineer jobs near you
Infographic showing various Ml Engineer job openings in Indiana as of July 2026, with employment types broken down into 92% Full Time, 5% Part Time, and 3% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $84,863 per year, or $40.8 per hour.

Staff ML Engineer

Group1001

Zionsville, IN • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 25 days ago

Group1001 rating

9.5

Company rating: 9.5 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

7th of 301 rated insurance

Job description

Group 1001 is a consumer-centric, technology-driven family of insurance companies on a mission to deliver outstanding value and operational performance by combining financial strength and stability with deep insurance expertise and a can-do culture. Group1001's culture emphasizes the importance of collaboration, communication, core business focus, risk management, and striving for outcomes. This goal extends to how we hire and onboard our most valuable assets - our employees.
*Please note, this position requires an in-person interview.
Why This Role Matters:
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
*Please note, this position requires an in-person interview.
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.

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