$150k - $180k
We have an immediate need for a Senior Electrical Engineer in Newton, MA. Come join our team! We are looking to build services and capabilities through the growth of our key asset- our staff. Ranked among the nation's to…
Engineering & IT · Boston, MA
Machine Learning Engineer jobs in Boston, MA
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
421
Open roles today
$55–$141/hr
Typical pay range
$189k
Median, full-time
2
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01
Open machine learning engineer roles
12 shown of 421 · sorted by freshness
$161k - $246k
Description Job Description Overview: The ASUS Robotics & AI Center is seeking a Senior Machine Learning Engineer to join our global research and development team. This role centers on leading the design and delivery of…
company that designs and runs tech career learning programs for the US and Latin American... ...looking for the person who brings an AI and Machine Learning curriculum to life for students... ...sessions and office hours…
$115k - $140k
Intelligence Division researches and develops advanced analytics and machine learning- based solutions to solve challenging problems related to... ...security. Our team consists of passionate and motivated engineers with…
$197.3k - $225.1k
Overview Lead Machine Learning Engineer (Finance Tech - AI Enablement) At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. Our investments in technology infrastructur…
the world. You will work directly with and learn from scientists who have operated at the... ...This role sits at the intersection of machine learning research and the experimental teams... ...discovery. At many organiza…
in the world. Through a dynamic ecosystem of research, learning, and entrepreneurship that includes MBA, Doctoral,... ...education, noble purpose, and timeless legacy? As a Machine Learning and Generative AI Engineer on…
$144k - $192k
scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery. As a Machine Learning Engineer on the Data Mining team, your mission is to…
scene understanding, and you could work on any (or all!) of these components. As a Senior Staff ML Engineer, you will lead the development of machine learning algorithms that can range in influence from onboard autonomy…
We are looking for a Machine Learning Engineer to develop and improve machine learning systems focused on entity resolution, record matching, deduplication, and ranking. Responsibilities: • Design, train, and optimize ma…
Job Description Job Description Machine Learning Engineer – Computer Vision & Robotics Tycho.AI is redefining the future of autonomous intelligence. Spun out of MIT and backed by DoD contracts, we are building breakthrou…
$146k - $225k
, you'll have the opportunity to work with world-class ML engineers and research scientists to make self-driving vehicles a reality... ...value experiments based on collaborative input from other machine learning enginee…
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What machine learning engineers earn in Boston
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $55–$77 | $115k–$160k |
| Mid level | $77–$105 | $160k–$218k |
| Senior | $101–$141 | $211k–$294k |
Adjusted for the Boston 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
01
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
02
Senior ML Engineer
03
Staff ML Engineer
04
ML Platform Lead
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