I'm looking for a Senior or Lead AI/ML role at a product company where I can own GenAI and applied-ML delivery end to end and work on hard, high-scale problems. I do my best work with real technical ownership, a strong engineering culture, and the freedom to take ideas from prototype to production. Open to remote and hybrid roles, and comfortable collaborating across time zones.
Looking for a job
Samuel Davis
@samueldavis
AI/ML Lead | GenAI, Computer Vision & NLP | Building production LLM/VLM & agentic systems at scale
IndiaWhat I'm looking for
AI/ML Lead with 5 years of experience building and shipping production GenAI, Computer Vision, and NLP systems. Currently one of two technical leads driving a 7-engineer AI team, owning end-to-end GenAI capability delivery for enterprise clients.
I've deployed compliance-grade, on-prem Vision-Language Models on constrained GPU hardware (Qwen3-30B on a single A100 via vLLM), built multilingual document-extraction and agentic LLM systems scaled across 8+ clients (95% field-level accuracy, 10K+ documents at ~75% straight-through processing), and re-architected core infrastructure into a single configurable platform on Prefect.
My strength is turning hurried prototypes into reusable, well-architected products. I'm strong across the full ML lifecycle: model development and fine-tuning, LLM and agentic applications (LangGraph, RAG, MCP), MLOps, and cloud/on-prem deployment on AWS and Kubernetes.
Open to Senior/Lead AI roles at product companies solving hard, high-scale problems
Experience
Work history, roles, and key accomplishments
Current
AI Lead
E42
Nov 2024 - Present (1 year 9 months)
Co-lead a 7-engineer AI team, owning end-to-end GenAI delivery for enterprise clients. Built a multilingual VLM invoice-extraction agent across ~8 clients (95% field accuracy, 10K+ docs, ~75% STP). Deployed compliance-grade on-prem redaction (Qwen3-30B on a single A100 via vLLM). Re-architected 9 client branches into one configurable platform on Prefect, cutting onboarding overhead.
Delivered production ML for QDox (Intelligent Document Processing) across 4+ clients on AWS (SageMaker, Lambda, SQS, DynamoDB, RDS) with OCR. Led an Auto Tagging solution that cut manual tagging ~90%. Built GenAI RAG, chatbot and SQL features. Optimized GPU and FAISS for a ~300% latency cut in face recognition, and built sports player tracking.
ML R&D intern. Generated large-scale synthetic datasets using Unreal Engine and UnrealCV for object detection, instance segmentation, and object tracking. Trained and evaluated detection and tracking models across real and synthetic data combinations to benchmark accuracy and data efficiency. Tools: YOLOv5, Detectron, FairMOT.
Education
Degrees, certifications, and relevant coursework
Fr. Conceicao Rodrigues College of Engineering
Bachelors, Computer Engineering
2017 - 2021
Grade: 8.97
Availability
Looking for a job
Location
IndiaAuthorized to work in
Salary expectations
3800k-4800k INR
Job categories
Skills
PythonAWSKubernetesTransformersLLM AI Agent FrameworksComputer VisionGoDockerCommunication SkillsNLPNatural Language ProcessingPyTorchDistributed TrainingAWS SagemakerAWS LambdaDynamoDBRDSFaissLang ChainPEFTVector StoresEasyOCRfastAPIFlaskMLFlowWeights BiasesLayoutLMBERTDeBERTaDonutDetectron2Flan T5BedrockResNetDenseNetSVHNTrackNetUnrealCVSynthetic Data GenerationOCR IntegrationAgentic SystemsInformation RetrievalCUDADjangoGitHubSQLUnreal EngineAgentic AI
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