Salary
≈ $24k – $49k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior · 7+ years exp
First seen by Alion on Oct 24, 2026.
Overview
Company
Impact
Profile match
Lytx is a technology company that designs, manufactures and sells video-based driver safety and fleet management solutions for commercial and public-sector fleets to help improve business productivity.
Backed by Insight Partners, Menlo Ventures, JMI Equity
As our Sr. Machine Learning Scientist, you will join our Applied Machine Learning Team in India, which 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!
Responsibilities:
- 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 services.
- Other duties as assigned.
Requirements:
- Bachelor's, MS or PhD in CS, Statistics, EE, or a related quantitative field.
- 7+ 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, and mixed-precision training.
- Strong experience managing large-scale ML dataset storage architecture, versioning (DVC, LakeFS, or custom), sampling strategies, and data quality workflows at terabyte 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.
Skills
AWS, CUDA, ML, MLOps, SQL, computer vision, machine learning, python
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