Job Description
Position: Autonomous Systems Performance Engineer
Function: Robotics and Autonomous Systems
Industry: Machine Learning
Grade: mid level
Location: Hybrid - Bengaluru
Employment Type: Full-time (WFH)
Compensation: INR 25.2-39.1 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with robotics and autonomous systems, in accordance with the standards and processes laid down by Machine Learning.
Minimum Qualification: M.Sc (Data Science)
Minimum Experience: 7 years
Core Competencies Required: Robotics and Autonomous Systems, TensorFlow/PyTorch, Feature Engineering, Python, MLOps, Model Evaluation & Tuning, Data Preprocessing
Further Information:
The organisation has historically promoted from within for a majority of its senior and lead openings. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. High performers in this role typically move into a broader ownership scope within 18-24 months. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. The next logical step from this position is a senior or lead-track role within the same function. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Interested candidates should be prepared to walk through relevant past work during the interview process. Mornings are usually spent on planning and status reviews, while the rest of the day is given over to hands-on delivery and problem-solving. Relocation assistance may be extended for candidates moving from a different city, subject to approval. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.
Function: Robotics and Autonomous Systems
Industry: Machine Learning
Grade: mid level
Location: Hybrid - Bengaluru
Employment Type: Full-time (WFH)
Compensation: INR 25.2-39.1 LPA
The organisation invites applications for the above-referenced position. The incumbent shall be responsible for discharging duties associated with robotics and autonomous systems, in accordance with the standards and processes laid down by Machine Learning.
Minimum Qualification: M.Sc (Data Science)
Minimum Experience: 7 years
Core Competencies Required: Robotics and Autonomous Systems, TensorFlow/PyTorch, Feature Engineering, Python, MLOps, Model Evaluation & Tuning, Data Preprocessing
Further Information:
The organisation has historically promoted from within for a majority of its senior and lead openings. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy. High performers in this role typically move into a broader ownership scope within 18-24 months. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. The next logical step from this position is a senior or lead-track role within the same function. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. The role alternates between independent deep work and short coordination huddles with stakeholders across functions. Interested candidates should be prepared to walk through relevant past work during the interview process. Mornings are usually spent on planning and status reviews, while the rest of the day is given over to hands-on delivery and problem-solving. Relocation assistance may be extended for candidates moving from a different city, subject to approval. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager.