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).