Machine Learning Operations Engineer at SatSure

Short Description:

SatSure, a decision intelligence company focused on agriculture, infrastructure, and climate action, is seeking a Machine Learning Operations Engineer in Bangalore, India. The role involves building and integrating large-scale machine learning systems, enhancing GPU training approaches, and developing software to improve experimentation. Responsibilities also include training and debugging deep learning models, architecting MLOps platforms, and collaborating across functions. The ideal candidate has 3+ years of experience, proficiency in ML frameworks, familiarity with GPU computing, and strong software engineering skills. The company offers a flat organizational structure, competitive leave policy, and additional allowances for learning and development.

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Position: Machine Learning Operations Engineer

Type: Full time

Location: Banglore, India

Experience: 3 - 6 Years

 

About SatSure

SatSure is an innovative decision intelligence company operating at the intersection of agriculture, infrastructure, and climate action, with a mission to create a positive impact in the developing world. We aim to democratize insights derived from earth observation data, making them accessible to a wide audience.

If you are passionate about contributing to societal impact through cutting-edge technology in an environment that encourages innovation, creativity, and a flat organizational structure, SatSure welcomes you to join our team.

Responsibilities:

• Develop and integrate end-to-end lifecycles for large-scale, distributed machine learning systems using the latest open-source technologies.
• Enhance distributed cloud GPU training methods for deep learning models.
• Create software that facilitates experimentation and aids in decision-making for future trials.
• Train, evaluate, and troubleshoot deep learning models for complex tasks.
• Create tools and services to enhance machine learning systems beyond modeling aspects.
• Handle data distribution editing, improve data quality, and implement representation learning with self-supervision.
• Architect the end-to-end platform supporting MLOps.
• Collaborate with cross-functional engineers to address complex data challenges at scale.
• Identify and assess new patterns and technologies to enhance the performance, maintainability, and elegance of machine-learning systems.
• Lead technical projects, communicating with peers to establish requirements and track progress.
• Mentor fellow engineers, contributing to a team culture that values effective collaboration, technical excellence, and innovation.

Requirements:

Must have:

• 3+ years of professional experience.
• Proficiency in ML modeling frameworks (e.g., PyTorch, Tensorflow).
• Experience in ML model serving (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.).
• Familiarity with GPU computing.
• Strong software engineering skills in complex, multi-language systems, with fluency in Python.
• Experience building end-to-end data systems as an ML Engineer, Platform Engineer, or equivalent.
• Familiarity with cloud data processing technologies (AWS, Spark, Dask, ElasticSearch, Presto, SQL, etc.).

Competencies:

• Excellent debugging and critical thinking skills.
• Outstanding analytical and problem-solving skills.
• Ability to thrive in a fast-paced, team-based environment.

Educational Qualifications:

• Bachelors, Masters, or PhD Degree in Computer Science/Machine Learning, SW Engineering.

Benefits:

Why Us?

• Opportunity to work with a unique and futuristic technology setup.
• Flat organizational structure and accessibility.
• Best-in-class leave policy.
• Additional allowances for learning, skill development, broadband, medical insurance cover, etc.

Please click here to apply.

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