Lytx
Senior Machine Learning Scientist
Skills
3 months ago
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Important information
Contract type:
Permanent
Salary:
₹3,500,000 – ₹4,500,000 / year
Location:
Bengaluru, Karnataka, India
Work mode:
Hybrid
Published on:
7 August 2026
What they need
Why Lytx?:
As our Sr Machine Learning Scientist, you will join our Applied Machine Learning Team in India, who develops machine learning and computer vision algorithms to monitor and assess the state of drivers and their environments to identify risk and improve safety for our clients. You will contribute to all aspects of the DL/ML model development and deployment cycle to improve the accuracy and throughput at reduced latency to help enhance and differentiate us as the leader in the Video Safety and Telematics industry. If this sounds like you, we encourage you to apply!
What You'll Do:
- Collaborate closely with product teams throughout the entire ML feature lifecycle, from defining requirements to delivering value to clients.
- End-to-End development of DL/ML models prototyping, formulation, data engineering, model training, etc.
- Implement, debug, and improvise DL/ML models.
- Develop and optimize cloud/Edge deployment of DL/ML service.
- Other duties as assigned.
What You'll Need:
- Bachelor’s, MS or PhD in CS, Statistics, EE, or a related quantitative field.
- 6+ years of applied ML experience, including production model development in a commercial setting.
- Proven experience with distributed training at scale — multi-GPU/multi-node training, memory optimization, gradient checkpointing, mixed-precision training.
- Strong experience managing large-scale ML datasets — storage architecture, versioning (DVC, LakeFS, or custom), sampling strategies, and data quality workflows at Terrabyte scale.
- Solid computer vision background: object detection, classification, video understanding, or multi-task models.
- Experience with cloud ML platforms (AWS preferred) and MLOps tooling
- Strong Python skills; familiarity with C++/CUDA or other performance-oriented tooling is a plus.
- SQL proficiency and comfort working with large-scale structured data (Redshift, Snowflake, or similar).
- Track record of independently driving ambiguous problems to clear technical outcomes.
- Strong communication skills; ability to present complex technical work to non-specialist stakeholders.
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