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Senior Machine Learning Engineer

carnow United State
Remote
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AI Summary

We're seeking an experienced Machine Learning Engineer to develop and deploy models from concept to production. The ideal candidate will have a strong background in machine learning and software development. Key requirements include 5+ years of experience building and shipping ML models to production.

Key Highlights
Rapidly prototype proof-of-concept models
Take models from proof-of-concept to production
Collaborate with cross-functional teams
Key Responsibilities
Rapidly prototype proof-of-concept models to test hypotheses and validate business value
Build, train, and tune models using algorithms like XGBoost, gradient boosting, and other classical/deep learning approaches
Take POCs all the way to production—deployment, monitoring, retraining, and optimization
Technical Skills Required
Python Machine Learning Data Pipelines
Benefits & Perks
Competitive compensation: $180K–$200K
Fully remote with flexible hours
Ownership of real ML problems
Nice to Have
Experience with MLOps tooling (Docker, Kubernetes, MLflow, Airflow)
Background in [NLP / computer vision / recommender systems / LLMs]
Contributions to open-source ML projects

Job Description


CarNow, Inc · Remote


About the Role

We're looking for an experienced Machine Learning Engineer to take models from idea to impact. You'll rapidly build proof-of-concept models, validate them against real business problems, and then do the hard part well—taking them all the way to production. This is a fully remote role for someone who's shipped ML systems before and knows what it takes to make them reliable at scale.


What You'll Do

  • Rapidly prototype proof-of-concept models to test hypotheses and validate business value
  • Build, train, and tune models using algorithms like XGBoost, gradient boosting, and other classical/deep learning approaches
  • Take POCs all the way to production—deployment, monitoring, retraining, and optimization
  • Design and maintain robust data and model pipelines
  • Partner with product, data, and engineering teams to define problems and deliver measurable results
  • Write clean, well-tested, production-grade Python code


What We're Looking For

  • 5+ years of experience building and shipping ML models to production
  • Strong programming skills in Python and its core ML ecosystem (NumPy, pandas, scikit-learn, XGBoost, PyTorch and/or TensorFlow)
  • Proven track record of moving models from proof-of-concept to production
  • Solid grasp of ML fundamentals: feature engineering, model training, evaluation, and tuning
  • Experience with data pipelines, APIs, and cloud platforms (AWS / GCP / Azure)
  • Strong problem-solving skills and clear communication with technical and non-technical partners


Nice to Have

  • Experience with MLOps tooling (Docker, Kubernetes, MLflow, Airflow)
  • Background in [NLP / computer vision / recommender systems / LLMs]
  • Contributions to open-source ML projects


Why Join Us

  • Competitive compensation: $180K–$200K plus [benefits, equity, PTO]
  • Fully remote with flexible hours
  • Ownership of real ML problems from prototype through production

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