
Senior Machine Learning Engineer
2 days ago
Job Title: Machine Learning Advisor
Location: Remote
Position Type: Part-Time (20 hours/week)
Experience Level: Senior (8 to 10+ years)
About the Role:
We are looking for a hands-on Machine Learning Advisor who can both build initial models and mentor our junior engineers as they refine and productionize them. This is a part-time role designed for a senior professional who enjoys rolling up their sleeves to prototype and code, while also providing strategic guidance, architecture oversight, and mentorship.You will help us establish a solid ML foundation by:
- Building and validating the first versions of our models.
- Setting up the right processes, frameworks, and best practices.
- Working closely with junior team members to fine-tune, scale, and optimize models.
This role is ideal for someone who thrives in a builder + advisor hybrid capacity, balancing hands-on contributions with leadership and mentorship.
Key Responsibilities
Hands-On Model Development
Design and build the initial versions of ML models (regression, classification, clustering, or deep learning, depending on problem type).
- Perform feature engineering, experimentation, and hyperparameter tuning.
Develop clean, scalable code for model training and inference.
Mentorship & Refinement
Work with junior ML engineers to iterate, refine, and fine-tune models.
- Review their code, guide debugging, and introduce advanced techniques.
Transfer knowledge and upskill the team for long-term ownership.
Architecture & Best Practices
Define the ML project workflow (from data prep to deployment).
- Set up reproducibility, versioning, and experiment tracking.
Recommend scalable approaches for data pipelines and model serving.
Collaboration
Partner with product and engineering to align ML solutions with business needs.
Communicate model performance, limitations, and trade-offs clearly to both technical and non-technical stakeholders.
8 to 10+ years of professional experience in machine learning, including building and deploying models.
- Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and ML frameworks (TensorFlow, PyTorch, or Keras).
- Experience designing end-to-end ML workflows, from feature extraction to deployment.
- Solid knowledge of ML algorithms, evaluation metrics, and optimization techniques.
- Hands-on experience with SQL and big data tools (Spark, PySpark).
- Familiarity with ML lifecycle tools (MLflow, Weights & Biases, DVC, Git).
- Strong track record of mentorship and technical leadership.
Preferred Qualifications (Good to Have)
- Experience with cloud ML platforms (AWS SageMaker, GCP Vertex, Azure ML).
- Exposure to deploying ML models as APIs (FastAPI, Flask).
- Familiarity with containerization (Docker, Kubernetes).
- Contributions to open-source ML projects or publications.
What We Offer
- A part-time, flexible role with high impact (20 hours/week).
- The opportunity to both build and mentor shaping the foundation of our ML team.
- A collaborative environment with motivated engineers eager to learn.
- Competitive compensation tailored for senior part-time talent.Role & responsibilities
Preferred candidate profile: Who are interested in Part time to handle a team and who can join in a week notice.
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