Job Description
Position: Computer Vision Platform Engineer
Function: Computer Vision
Industry: Machine Learning
Grade: mid level
Location: Kochi
Employment Type: Hybrid
Compensation: INR 15.9-37.4 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with computer vision, in accordance with the standards and processes laid down by Machine Learning.
Minimum Qualification: M.Tech (Machine Learning)
Minimum Experience: 4 years
Core Competencies Required: Model Evaluation & Tuning, TensorFlow/PyTorch, Computer Vision, Computer Vision/NLP Basics, Python, MLOps, Statistical Modelling
Further Information:
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Interested candidates should be prepared to walk through relevant past work during the interview process. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. High performers in this role typically move into a broader ownership scope within 18-24 months. The organisation has historically promoted from within for a majority of its senior and lead openings. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Most days include at least one review checkpoint where progress is discussed against the plan for the week. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.
Function: Computer Vision
Industry: Machine Learning
Grade: mid level
Location: Kochi
Employment Type: Hybrid
Compensation: INR 15.9-37.4 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with computer vision, in accordance with the standards and processes laid down by Machine Learning.
Minimum Qualification: M.Tech (Machine Learning)
Minimum Experience: 4 years
Core Competencies Required: Model Evaluation & Tuning, TensorFlow/PyTorch, Computer Vision, Computer Vision/NLP Basics, Python, MLOps, Statistical Modelling
Further Information:
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. Interested candidates should be prepared to walk through relevant past work during the interview process. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction. High performers in this role typically move into a broader ownership scope within 18-24 months. The organisation has historically promoted from within for a majority of its senior and lead openings. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Most days include at least one review checkpoint where progress is discussed against the plan for the week. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions.