FACILITIES ENGINEER POSITION SUMMARY The Facilities Engineer provides engineering and... ...applicable safety, electrical, environmental, machine- guarding, Lockout/Tagout (LOTO), and... ...excellence and renewable energ…
Engineering & IT · Indianapolis, IN
Machine Learning Engineer jobs in Indianapolis, IN
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
119
Open roles today
$40–$103/hr
Typical pay range
$137k
Median, full-time
10
Fresh in this list
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01
Open machine learning engineer roles
12 shown of 119 · sorted by freshness
We are looking for a Systems Engineer to support and enhance core enterprise infrastructure in Indianapolis, Indiana. This Long-term Contract position is ideal for a detail-oriented candidate with strong experience with…
$85.6k - $149.4k
Sentri7 Drug Diversion platform. Working closely with product, engineering, data science, and customer-facing teams, this role helps... ...professional experience in data science, predictive modeling, or machine learning…
$98.96k - $120.96k
Job Description:NVH Test Engineer* Collaborate with Innovative 3Mers Around the WorldChoosing where to start and grow your career has a... ...during their employment, and for a period after they leave 3M. Learn more abou…
with integrity, respect, responsibility, and professionalism.Vertex, located in Indianapolis, IN, is seeking a Senior Electrical Engineer I to support development, integration, and sustainment of ground‑based electronic…
$98.57k - $160.17k
to one of the world’s most recognized brands and a beacon for engineering excellence.Position SummaryAn exciting opening for a Joining &... ...technologies that move us forward. If you’re driven to grow, to learn, and to…
$133.5k - $224.4k
experienced Senior Principal Data, Analytics & AI Engineer to join the Global DIA team within MQ... ...and agentic AI.Agentic AI and machine learningClosely collaborate with the business... ....Implement, test, and deplo…
DescriptionAt HDR, we specialize in engineering, architecture, environmental and construction services. While we are most well-known for adding beauty and structure to communities through high-performance buildings and s…
$122.76k - $220.97k
: ANA United StatesWork Type: HybridDate Posted: 2026-09-03Arcadis is the world's leading company delivering sustainable design, engineering, and consultancy solutions for natural and built assets.We are more than 34,000…
throughout our company and within our communities, we constantly ask ourselves: What is our impact on the world?We believe building engineering is more than systems and structures, it’s about powering progress and enabli…
are a team of Innovators, Collaborators and Doers. We’re seeking a Senior ML Engineer to join us. As a Senior ML Engineer at Zotec, you will build and extend the machine learning and AI systems that give our teams direct…
whatever your ambitions. About the role: As a Field Service Engineer at Boston Scientific, you will serve as a trusted technical... ...at Boston Scientific? Check out our video featuring Bob to learn more about the role:…
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What machine learning engineers earn in Indianapolis
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $40–$56 | $84k–$116k |
| Mid level | $56–$76 | $116k–$158k |
| Senior | $74–$103 | $153k–$214k |
Adjusted for the Indianapolis market from national ranges.
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What employers ask for
The skills these listings keep naming
Python and software engineeringPyTorch or TensorFlowML fundamentals and evaluationModel serving and APIsMLOps (tracking, registries, CI)Docker and KubernetesData pipelines and feature storesLLM fine-tuning and RAG (a plus)Monitoring and drift detection
04
Interview questions worth rehearsing
With the thing the interviewer is actually listening for
Walk me through taking a model from prototype to production.
Cover data pipelines, training reproducibility, serving, and monitoring. Emphasize that the model is a small part of the system — that framing is the job.
How do you monitor a model in production?
Discuss input drift, prediction distributions, delayed labels, and business metrics — plus what triggers retraining. Mention that silent degradation is the default failure mode.
How would you reduce inference latency or cost for a large model?
Options include distillation, quantization, batching, caching, and smaller models. Frame it as measuring first, then choosing the cheapest acceptable quality tradeoff.
Tell me about a time a model failed in production. What happened?
A real story about skew, drift, or a data bug — with detection and prevention — is far more convincing than claiming smooth deployments.
How do you evaluate a model beyond accuracy?
Talk about the metric matching the business cost of errors, slicing by segment, and offline-online gaps. Naming a case where accuracy misled is a strong touch.
When would you fine-tune an LLM versus use retrieval or prompting?
Start cheap: prompting, then RAG for knowledge, fine-tuning for behavior and format. Cost and maintenance burden should drive the answer.
How do you make training reproducible?
Version code, data, and config; track experiments; pin environments. This is engineering discipline applied to ML, which is exactly the role.
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Resume tips that move the needle
For machine learning engineers specifically — generic advice costs you here
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Center bullets on production systems: models served, request volume, latency, and the business metric they moved.
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Show software engineering credentials explicitly — testing, CI, code review — since MLE hiring filters hardest on engineering rigor.
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Name the MLOps tooling you have run (MLflow, SageMaker, Kubeflow, vector databases) as these are common screens.
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Include LLM work with specifics — fine-tuning, RAG, evaluation — if you have it; vague 'GenAI experience' claims read poorly.
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Distinguish your role on shared projects: built the serving layer, owned the pipeline, or trained the model.
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Where this role goes
Typical progression
01
ML Engineer
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Senior ML Engineer
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Staff ML Engineer
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ML Platform Lead
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