Senior Machine Learning Engineer

Kake is looking for an experienced Senior Machine Learning Engineer to design and deliver production-grade ML solutions that create real impact. In this remote role, paid in USD, you’ll work on challenging problems across a variety of domains, owning work from architecture and experimentation through deployment at scale. The ideal candidate has deep expertise in Python and modern ML frameworks, a proven track record of taking models to production, and the confidence to drive technical work with minimal oversight. If you’re a seasoned engineer looking for your next challenge with a forward-thinking team, we’d love to hear from you.

Key Responsibilities

• Lead the end-to-end design, development, and deployment of scalable machine learning systems in production.
• Architect robust ML pipelines and infrastructure, making key decisions on tooling, frameworks, and best practices.
• Partner with stakeholders to translate business goals into technical roadmaps and well-scoped ML solutions.
• Own model performance, reliability, and monitoring in production, proactively identifying and resolving issues.
• Mentor and guide other engineers through code reviews, technical feedback, and knowledge sharing.
• Drive experimentation strategy and evaluate new techniques, research, and tools to keep solutions at the cutting edge.
• Communicate technical trade-offs and results clearly to both technical and non-technical audiences.

Core Requirements

• 5+ years of professional experience in machine learning engineering, with a strong track record of production deployments.
• Expert-level proficiency in Python and deep experience with PyTorch, TensorFlow, or similar frameworks.
• Strong command of ML fundamentals and advanced techniques, including deep learning, model optimization, and evaluation at scale.
• Proven experience designing and maintaining ML infrastructure on cloud platforms (AWS, GCP, or Azure).
• Solid software engineering skills, including system design, testing, CI/CD, and writing clean, maintainable code.
• Strong experience with SQL, distributed data processing (e.g., Spark), and large-scale datasets.
• Excellent written and verbal communication skills in English.
• Ability to work independently in a remote, fast-paced environment.

Nice-to-Have

• Hands-on experience with LLMs, fine-tuning, RAG systems, or generative AI applications.
• Deep familiarity with MLOps tooling such as MLflow, Kubeflow, Airflow, or Weights & Biases.
• Experience with Docker, Kubernetes, and real-time model serving (e.g., Triton, TorchServe, Ray Serve).
• Prior experience as a tech lead or in a client-facing / consulting role.
• Published research, patents, or significant open-source contributions.

Additional

• US Timezone Overlap Required (EST/PST).