AI/ML Tech Lead

TechotlistContract
Remote
8 - 12 YearsFeb 6th, 2026
64 ViewsBe an Early Applicant
Required Skillset:
Gen AI

Job Description

Position: AI/ML Tech lead with hands on experience on Gen AI
Location: Remote
Job Description:  

Designing and deploying scalable, secure, and reliable LLM-based solution,  implement Retrieval-Augmented Generation (RAG), model fine-tuning, and agentic workflows to solve complex business problems. 
Key Responsibilities
Design, build, and maintain production-grade Generative AI applications and APIs on GCP, focusing on Gemini models, RAG architectures, and vector databases.
Develop automated MLOps pipelines (training, evaluation, monitoring, deployment) using Vertex AI, Kubeflow, Cloud Build, and Terraform.
Implement techniques to enhance AI model performance, including fine-tuning, quantization (e.g., GPTQ, AWQ), and prompt engineering to improve accuracy and reduce latency.
Optimize GCP resources for high-performance computing, ensuring scalability, cost-efficiency, and security (IAM, VPC).
Partner with Data Science, Data Engineering, and Product teams to translate business requirements into technical AI/ML roadmaps.
Ensure compliance with data privacy, security regulations (HIPAA, GDPR, if applicable), and ethical AI standards. 

Required Qualifications
5-8+ years of industry experience in Machine Learning, with at least 3+ years of hands-on experience in building and deploying Generative AI models and LLMs in a production environment.
Proven experience with Google Cloud Platform (GCP) and its AI suite (Vertex AI, BigQuery, Dataflow, Cloud Run).
Strong expertise in Python and standard data science libraries (scikit-learn, TensorFlow, PyTorch).
Hands-on experience with framework tooling such as LangChain, LlamaIndex, or Hugging Face.
Strong understanding of SQL and unstructured data management.
Familiarity with Docker, Kubernetes (GKE), and CI/CD tools. 

Preferred Qualifications
Experience with multi-agent systems and orchestration (e.g., LangGraph, AutoGen).
Deep knowledge of Vector Databases (e.g., Vertex AI Vector Search, Pinecone, Chroma).
Google Cloud Professional Machine Learning Engineer certification.
Demonstrated experience leading team projects and mentoring junior engineers.

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