Design, develop, and deploy generative AI models and related solutions within Infosys’ global delivery ecosystem.
Compensation
Along with competitive pay, as a full-time Infosys employee you are also eligible for the following benefits: Medical/Dental/Vision/Life Insurance, Long-term/Short-term Disability, Health and Dependent Care Reimbursement Accounts, Insurance (Accident, Critical Illness , Hospital Indemnity, Legal), 401(k) plan and contributions dependent on salary level, Paid holidays plus Paid Time Off
Responsibilities
Analyze user stories and use cases to ensure accurate understanding for production-ready delivery
Contribute to define design specifications and technology frameworks and assist in creation of reusable assets
Deliver high-quality, optimized and efficient code across applications and databases, engage in debugging complex routines and build automation
Support the team to foster a robust technical environment and ensure error-free coding
Participation in knowledge transfer sessions and assist in utilizing reverse engineering methodologies to support the transition process
Requirements
Bachelor’s degree or foreign equivalent
Nice to have: cloud-based platforms like OpenShift
Design and build AI/ML applications and systems, integrating cloud or on-prem pipelines, applying generative AI models, and leading cross‑functional teams to deliver production‑ready solutions.
Responsibilities
Lead design and implementation of AI‑driven solutions
Lead and support an engineering team focused on building production-grade deep learning models for autonomous driving.
Compensation
The expected base salary range for this full-time position in California is $218,240 - 327,360 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.
Responsibilities
Lead and mentor engineers across levels
Own sprint planning, roadmap execution, and technical delivery of unified multi-sensor models
Provide architectural and modeling guidance across spatio-temporal deep learning, multi-sensor fusion, and multi-task learning networks
Partner closely with downstream autonomy teams to align on output formats, latency budgets, and interface contracts
Work closely with adjacent infrastructure partners to ensure efficient distributed training and optimized onboard runtime execution
Requirements
Bachelor's degree in Computer Science, Computer Engineering, Robotics, Electrical Engineering, or related field
Master's degree in Computer Science, Computer Engineering, Robotics, Electrical Engineering, or related field
Ph.D. in Computer Science, Computer Engineering, Robotics, Electrical Engineering, or related field
Nice to have: Ph.D. with a machine learning or computer vision focus
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution.
Responsibilities
Expected to be an SME, collaborate and manage the team to perform.
Responsible for team decisions.
Engage with multiple teams and contribute on key decisions.
Provide solutions to problems for their immediate team and across multiple teams.
Lead the development and deployment of AI models ensuring alignment with project goals and timelines.
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Applies Generative AI models as part of the solution.
Locations (2)
Bengaluru, Karnataka, India
Pune, Maharashtra, India
Responsibilities
Expected to be an SME, collaborate and manage the team to perform.
Responsible for team decisions.
Engage with multiple teams and contribute on key decisions.
Provide solutions to problems for their immediate team and across multiple teams.
Lead the development and deployment of AI models ensuring alignment with project goals and timelines.
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Responsibilities
Expected to be an SME, collaborate and manage the team to perform.
Responsible for team decisions.
Engage with multiple teams and contribute on key decisions.
Provide solutions to problems for their immediate team and across multiple teams.
Lead the development and deployment of AI models ensuring alignment with project goals and timelines.
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