Data Scientist

LTM; Edison (NJ); On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Comprehensive Medical Plan

401(k) Plan with Company match

Paid Holidays

Job summary

LTIMindtree is seeking Applied Scientists at Lead/IC levels to design and optimize GenAI-driven multimodal pipelines for detecting contextual moments in live video streams. You will work on prompt strategies, multimodal inference, and structured outputs to integrate GenAI results into downstream systems.

The role emphasizes hands-on experience with AWS Bedrock, Lambda, S3, and Kinesis, plus collaboration with QA for production rollout and continuous improvement.

Qualifications

• Prompt engineering for foundation models like Claude Nova, etc.
• Multimodal AI systems including vision and NLP.
• Strong Python programming and data pipeline skills.
• Hands-on experience with LLM inference and optimisation.

Responsibilities

• Design and optimise prompt engineering strategies for foundation models.
• Build pipelines for multimodal inference (video transcript, audio).
• Detect and classify contextual moments and custom events.
• Develop reusable frameworks and moment detection templates.

Skills

Prompt engineering

Multimodal AI

Python

Video analytics

LLM inference

Tools

AWS Bedrock

Lambda

S3

Kinesis

Job description

Role Description

Role OverviewWe are hiring Applied Scientists 1 Lead 2 ICs to design build and optimise GenAIdriven multimodal pipelines for detecting contextual moments in live video streams

Key Responsibilities

• Design and optimise prompt engineering strategies for foundation models
• Build pipelines for multimodal inference video transcript audio
• Detect and classify custom moments and contextual events
• Develop reusable frameworks for
• Moment detection templates
• Structured metadata generation
• Finetune prompts and configurations to improve
• Accuracy
• Precision across moment types
• Integrate GenAI outputs into
• Structured JSON metadata
• Downstream systems and pipelines
• Work with AWS services such as Amazon Bedrock GenAI models Lambda S3 Kinesis data pipeline
• Collaborate with QA team for output validation and optimisation
• Support production rollout and continuous improvement

Required Skills Experience

• Strong experience in
• Prompt engineering for foundation models Claude Nova etc
• Multimodal AI systems vision NLP
• Handson experience with
• LLM inference and optimisation
• Structured outputs JSON generation and validation Strong Python programming and data pipeline skills
• Familiarity with AWS cloud stackBedrock Lambda S3 analytics pipeline
• Experience in working withVideo analytics media AI workflows Realtime or near realtime systems

Other Details

Variable Compensation: This position includes a bonus or variable payout component based on individual and organizational performance. Actual compensation within the range will be dependent upon the individual's skills, experience, performance and internal equity.

Benefits And Perks

• Comprehensive Medical Plan Covering Medical, Dental, Vision
• Short Term and Long-Term Disability Coverage
• 401(k) Plan with Company match
• Life Insurance
• Vacation Time, Sick Leave, Paid Holidays
• Paid Paternity and Maternity Leave

The range displayed on each job posting reflects the minimum and maximum salary target for the position across all US locations. Within the range, individual pay is determined by work location and job level and additional factors including job-related skills, experience, and relevant education or training. Depending on the position offered, other forms of compensation may be provided as part of overall compensation like an annual performance-based bonus, sales incentive pay and other forms of bonus or variable compensation.

Disclaimer

The compensation and benefits information provided herein is accurate as of the date of this posting.

LTIMindtree

is an equal opportunity employer that is committed to diversity in the workplace. Our employment decisions are made without regard to race, color, creed, religion, sex (including pregnancy, childbirth or related medical conditions), gender identity or expression, national origin, ancestry, age, family-care status, veteran status, marital status, civil union status, domestic partnership status, military service, handicap or disability or history of handicap or disability, genetic information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation or preference, or any other characteristic protected by applicable federal, state, or local law, except where such considerations are bona fide occupational qualifications permitted by law.