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Junior Machine Learning Jobs in Indiana (NOW HIRING)

Collaborate in Agile/Scrum workflows, mentor junior engineers, and lead design/code reviews to sustain longterm maintainability. Required Qualifications and Experience: * BS/MS in Machine Learning ...

Junior Mechanical Engineer

Crane, IN · On-site

$47K - $95K/yr

Draft detailed multi-view drawings of systems, machinery spaces, systems, assemblies and products ... We offer competitive compensation, benefits and learning and development opportunities. Our broad ...

Conduct research on emerging AI, machine learning, and advanced analytics techniques. * Participate ... Currently enrolled in an undergraduate program as a rising Junior or Senior, pursuing a degree in ...

Conduct research on emerging AI, machine learning, and advanced analytics techniques. * Participate ... Currently enrolled in an undergraduate program as a rising Junior or Senior, pursuing a degree in ...

As the Senior Machine Learning & Computer Vision Scientist, you will accelerate Elanco's R&D ... Provide technical leadership and mentorship by guiding junior scientists, leading crossfunctional ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... junior staff while upholding remarkable standards of quality and innovation in deliverables.

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Junior Machine Learning information

What does a junior machine learning engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

What are the key skills and qualifications needed to thrive as a junior machine learning engineer?

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.

What types of projects and tasks can a junior machine learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

What is the difference between Junior Machine Learning vs Data Scientist?

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

What are the most commonly searched types of Machine Learning jobs in Indiana?

The most popular types of Machine Learning jobs in Indiana are:

Infographic showing various Junior Machine Learning job openings in Indiana as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

AI Machine Learning Engineer Intern (BS)

Indianapolis, IN • On-site

$60 - $80/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago

New


Job description

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.

Organization Overview

At Lilly, we serve an extraordinary purpose. We make a difference for people around the globe by discovering, developing and delivering medicines that help them live longer, healthier, more active lives. Not only do we deliver breakthrough medications, but you also can count on us to develop creative solutions to support communities through philanthropy and volunteerism.

Responsibilities

You will join the Clinical and Development area within Lilly’s Advanced Intelligence & Research organization, where we build and deliver advanced AI and data science solutions that accelerate clinical development and improve decision‑making across the drug development lifecycle. Machine learning is central to that work. We build, deploy, and scale models and AI systems that support decisions across clinical development, ranging from predictive models trained on clinical and real‑world data to generative AI applications and agentic systems that put those capabilities directly in the hands of scientists and clinicians. Our engineers work across the full lifecycle: framing the problem, prototyping, evaluating rigorously, and building the pipelines and infrastructure that take a promising model from a notebook to something people rely on. As an intern, you will be assigned a scoped project with real business impact and will work alongside experienced machine learning engineers and research scientists. The work will draw on a common set of capabilities: training, tuning, and evaluating machine learning models; building and scaling the pipelines that support them; writing production‑quality Python; and translating methods and results for scientific and business partners. You might build generative AI applications, AI agents, or Model Context Protocol (MCP) integrations; develop predictive models on clinical or real‑world data; help scale and productionize model training and deployment pipelines; or prototype and evaluate newer methods against real clinical development problems. Lilly internships run for 12 continuous weeks over the summer. Each intern actively contributes to the organization, builds a comprehensive understanding of the pharmaceutical industry, and takes part in professional development and social events throughout the summer. At the conclusion of the internship, each intern presents their project highlights, findings, recommendations, and accomplishments to senior leaders and stakeholders. As part of Lilly's commitment to innovation, interns will have the opportunity to build fluency with AI tools used across the business. We expect interns to approach these tools with curiosity, apply critical thinking to AI‑assisted work, and always prioritize accuracy, confidentiality, and ethical standards in how they use them.

Basic Qualifications

Currently enrolled in and pursuing a Bachelor’s degree in Computer Science, Computer Engineering, Data Science, Statistics, Mathematics, Applied Mathematics, Electrical Engineering, or a closely related technical field, and will have completed your Junior year by June 2027. Qualified applicants must be authorized to work in the United States on a full‑time basis. Lilly will not provide support for or sponsor work authorization or visas for this role, including but not limited to F-1CPT, F-1OPT, F-1STEMOPT, J-1, H-1B, TN, O-1, E-3, H-1B1, or L-1.

Additional Skills / Preferences

Experience with at least one machine learning or deep learning framework, such as PyTorch, scikit-learn, or TensorFlow. Fundamental knowledge of machine learning principles and hands‑on experience programming in Python. Experience building applications with large language models, including prompt engineering, retrieval‑augmented generation, agent frameworks, Model Context Protocol (MCP), or systematic model evaluation. Experience training and evaluating predictive models on real datasets, including feature engineering, validation strategy, and interpreting results. Working knowledge of SQL and comfort handling large datasets; experience with Spark or PySpark, or a cloud data platform such as Databricks is a plus. Exposure to a major cloud provider, preferably AWS (for example SageMaker, Bedrock, S3, or Lambda). Familiarity with MLOps practices such as experiment tracking, model packaging and serving, monitoring, or workflow orchestration, using tools such as MLflow or Weights & Biases. Experience with Git‑based version control, code review, and automated testing or CI/CD; familiarity with Docker is a plus. Interest in healthcare, clinical, or life sciences applications of machine learning, or prior experience working with sensitive or regulated data. Ability to communicate methods and results clearly to both technical and non‑technical audiences. A demonstrated drive to learn, innovate, and challenge yourself for the benefit of patients. Prior experience using AI tools (e.g., generative AI platforms, automation tools, or AI‑assisted research/analytics tools) in an academic, project, or work setting.

Additional Information

This is a hands‑on applied machine learning engineering internship. Interns are expected to take ownership of a scoped project, write production‑quality code, collaborate closely with data engineers, research scientists, and clinical partners, and deliver a final presentation of their results to senior leaders and stakeholders. All interns will be considered for full‑time positions based on their internship performance. Lilly arranges various intern activities including sporting events, dinners, lunch and learns, volunteer activities etc. to provide opportunities for socializing, professional development, and learning more about Lilly. Interns will receive 1 week of paid time off during the Lilly summer shut‑down (July5th–July9th), 1:1 mentoring from an experienced professional in the function. Interns will receive a competitive salary and free parking at their work site, as well as access to Lilly’s LIFE fitness center, bike garage, and many other discounts. If the intern’s job position requires a move from another location, Lilly will provide subsidized housing. Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form https://careers.lilly.com/us/en/workplace-accommodation for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Employee Resource Groups (ERGs)

Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include:

  • Africa
  • Middle East
  • Central Asia (AMECA)
  • Black Employees at Lilly (BE@Lilly)
  • Chinese Culture Network (CCN)
  • EnAble
  • Evolve
  • Lilly Indian Network (LIN)
  • Organization of Latinx at Lilly (OLA)
  • Pride (LGBTQ+ Allies)
  • Veterans Leadership Network (VLN)
  • Women’s Initiative for Leading at Lilly (WILL)
EEO and Diversity

Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status. Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees.

Compensation and Benefits

Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is $65,600 (Bachelors) annually. Full‑time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company‑sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day‑care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well‑being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities). Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.

About Lilly

How do we do this? We continue to look for ways to include, innovate, accelerate and deliver while maintaining integrity, excellence and respect for people. We hope that you seek to join us on our journey as we create medicine and deliver improved outcomes for patients across the globe! #WeAreLilly

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