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Data Analytics & AI Services
Machine Learning Engineer
Remote Full-time 2-5 years Bachelor's Degree
Apply for this Position Position Overview
We are looking for an ML engineer to own models in production — training them reproducibly, serving them within a latency and cost budget, and noticing when they start to drift before a stakeholder does. This is the discipline of keeping models working, not of inventing them.
Key Responsibilities
- Own the production lifecycle of the models for a domain: training, deployment, monitoring, and retraining.
- Build reproducible training pipelines with versioned data, code, and parameters.
- Build feature pipelines that produce identical values offline and online, using Redis where low-latency lookups are needed.
- Deploy models as containerized services on Kubernetes within explicit latency and cost budgets.
- Instrument monitoring for data drift, prediction distribution, and the business metric the model is supposed to move.
- Set up retraining triggers and rollback so a bad model can be pulled in minutes, not days.
- Work with data scientists to turn a validated experiment into something operable.
- Own the performance of what you ship: batch throughput, tail latency, and inference cost.
Skills & Qualifications
- 2-5 years shipping machine learning to production.
- Strong Python with real engineering habits: tests, packaging, and CI.
- scikit-learn and PyTorch, plus the judgment to know when a simple model is the right answer.
- Docker and Kubernetes for deploying inference workloads.
- Model versioning and experiment tracking with MLflow or an equivalent.
- Production monitoring: drift detection, data quality checks, and service metrics.
- SQL and pipeline literacy — Airflow and warehouse data are part of the job.
Nice to Have
- Designing or operating a feature store.
- Model optimization for serving: batching, quantization, or ONNX export.
- Terraform for ML infrastructure.
- Streaming inference driven by Kafka events.
What You'll Gain
- Competitive salary.
- Fully remote — work from wherever you're most productive.
- Annual learning budget for books, courses, and conferences.
- Top-tier hardware and software tooling.
- Private health insurance and flexible time off.
Apply for this Position
Send your CV and a short cover letter. We'll reply by email.
Apply for this Position