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Machine Learning Engineer

A Machine Learning Engineer designs, trains, and deploys models that learn from data. They own the pipeline from feature engineering and experimentation to serving and monitoring in production. The role combines statistics and software engineering, turning research prototypes into scalable systems that make predictions reliably and improve as new data arrives.

Responsibilities

Build and train models for prediction, ranking, or classification
Engineer features and manage training and evaluation datasets
Deploy models as scalable, monitored production services
Run experiments and A/B tests to improve model performance
Optimize training and inference for speed and cost
Partner with data and platform teams on infrastructure

Must-have skills

Solid grasp of ML algorithms and model evaluation
Proficiency in Python and a framework such as PyTorch or TensorFlow
Experience with data pipelines and feature engineering
Model deployment and serving experience
Strong software engineering and testing practices

Nice-to-have skills

Distributed training on GPUs or TPUs
Experience with recommendation or ranking systems
Streaming or real-time inference
Familiarity with MLOps platforms

Average Salary

Typical US base salary for an HR Generalist by experience level.

Junior

0–2 yrs experience

$115,000 – $145,000
US annual salary (USD)

Intermediate

0–2 yrs experience

$145,000 – $185,000

US annual salary (USD)

Senior

0–2 yrs experience

$185,000 – $250,000

US annual salary (USD)

Figures are annual US market estimates for orientation, not offers. Actual pay varies by location, company stage, and equity.

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Frequently asked questions

What does a Machine Learning Engineer do day to day?
They spend time on data preparation, model training and evaluation, code review, and keeping deployed models healthy. Meetings with data scientists and product teams shape what to build next.
Machine Learning Engineer vs Data Scientist: what is the difference?
Data Scientists emphasize analysis, experimentation, and insight. Machine Learning Engineers emphasize building and shipping the production systems that run models at scale. Some companies blend the two.
What degree do you need to be a Machine Learning Engineer?
Many hold a degree in computer science, statistics, or a related field, but strong applied skills and a project portfolio can substitute. Advanced degrees help for research-focused roles.
Is Python enough for machine learning engineering?
Python is the core language, but you also need SQL, some systems knowledge, and comfort with cloud and container tools to ship models to production.

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