Senior Machine Learning Operations Engineer

4 weeks ago

Bengaluru, Karnataka, India SatSure Full time
About SatSure

SatSure is a pioneering deep tech company that harnesses the power of decision intelligence to drive meaningful impact in the realms of agriculture, infrastructure, and climate action. Our mission is to make earth observation data accessible to all, empowering a more sustainable future.

Job Summary

We are seeking a highly skilled Senior Machine Learning Operations Engineer to join our team. As a key member of our engineering team, you will be responsible for designing, building, and integrating large-scale, distributed machine learning systems. Your expertise will be instrumental in driving the development of cutting-edge tools and frameworks that enhance research experimentation and improve the performance, maintainability, and elegance of our machine learning systems.

Key Responsibilities
  1. Architect and build end-to-end life cycles of large-scale, distributed machine learning systems using cutting-edge tools and frameworks.
  2. Develop tools and services for explainability of ML solutions.
  3. Implement distributed cloud GPU training approaches for deep learning models.
  4. Build software/tools that improve the rate of experimentation for the research team and extract insights from it.
  5. Identify and evaluate new patterns and technologies to improve the performance, maintainability, and elegance of our machine learning systems.
  6. Lead and execute technical projects to completion.
  7. Communicate with peers to build requirements and track progress.
  8. Mentor fellow engineers in your areas of expertise.
  9. Contribute to a team culture that values effective collaboration, technical excellence, and innovation.
Qualifications

We are looking for a candidate with 5-8 years of professional experience in implementing MLOps frameworks to scale up ML in production. A Master's degree or PhD in Computer Science, Machine Learning/Deep Learning domains is required.

Must-Have Skills
  • Hands-on experience with Kubernetes, Kubeflow, MLflow, Sagemaker, and other ML model experiment management tools.
  • Experience in ML model serving (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.).
  • Proficiency with ML model training frameworks (PyTorch, PyTorch Lightning, TensorFlow, etc.).
  • Experience with GPU computing to do data and model training parallelism.
  • Solid software engineering skills in developing systems for production.
  • Strong expertise in Python.
  • Building end-to-end data systems as an ML Engineer, Platform Engineer, or equivalent.
  • Experience working with cloud data processing technologies (S3, ECR, Lambda, AWS, Spark, Dask, ElasticSearch, Presto, SQL, etc.).
Competencies
  • Excellent debugging and critical thinking skills.
  • Excellent analytical and problem-solving skills.
  • Ability to work in a fast-paced, team-based environment.
Benefits

We offer a comprehensive benefits package, including medical health cover for you and your family, access to mental health experts, dedicated allowances for learning and skill development, and a comprehensive leave policy.

Interview Process

The interview process will consist of an intro call, assessment, presentation, and interview rounds (ideally up to 3-4 rounds). A culture round/HR round will also be conducted to assess your fit with our team culture.

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