Machine Learning Enginee
2 weeks ago
About SatSure
SatSure is a deep tech, decision Intelligence company that works primarily at the nexus of agriculture, infrastructure, and climate action creating an impact for the other millions, focusing on the developing world. We want to make insights from earth observation data accessible to all.
If you are interested in working in an environment that focuses on the impact on society, driven by cutting-edge technology, and where you will have the freedom to work on innovative ideas and be creative with no hierarchies, SatSure is the place for you.
Roles and Responsibilities
- Build and integrate end to end lifecycles of large-scale, distributed machine learning systems using the latest open source technologies
- Improve distributed cloud GPU training approaches for deep learning model
- Build software that improves your rate of experimentation and helps you make better decisions about what to try next
- Train, evaluate, and debug deep learning models for complex tasks
- Develop tools and services for improving ML systems beyond modeling choices
- Data distribution editing, data quality improvements, and representation learning with self-supervision
- Architect the end-to-end platform that supports MLOps
- Collaborate with engineers across functions to solve complex data problems at scale
- Identify and evaluate new patterns and technologies to improve performance, maintainability and elegance of our machine learning systems
- Lead technical projects to completion. Communicate with peers to build requirements and track progress
- Mentor fellow engineers in your areas of expertise - Contribute to a team culture that values effective collaboration, technical perfection, and innovation
**Requirements**:
**Experience**:
- 3+ years of professional experience.
- Proficiency with ML modeling frameworks (PyTorch, Tensorflow, etc.).
- Experience in ML model serving (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.)
- Familiarity with GPU computing.
- Solid software engineering skills in complex, multi-language systems. Fluency in Python.
- Building end to end data systems as an ML Engineer, Platform Engineer, or equivalent.
- Experience working with cloud data processing technologies (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.
Educational Qualifications:
- Bachelors, Masters, or PhD Degree in Computer Science/Machine Learning, SW Engineering.
**Benefits**:
Why Us?
- Opportunity to work on 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.
Department Name
ML ops
Industry
Research & Development
City
Bangalore
State/Province
Karnataka
Country
India
Zip/Postal Code
560025
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