Associate Machine Learning Architect

Architect the Future of AI with goML

goML

bridge the gap between advanced AI research and real-world enterprise adoption

Associate ML Architect

If you're passionate about building production-grade AI systems and driving the next wave of enterprise GenAI innovation, we'd love to hear from you!

Why You Why Now

Generative AI is revolutionizing how businesses operate but scaling it requires strong architecture, security, and performance foundations.

architecting AI/ML workloads

At goML, You Will:

• Architect and own end-to-end

  AI/ML and GenAI solutions

  across industries.
• Collaborate with

  sales, presales, and engineering

  teams to define technical proposals.
• Design

  cloud-native, multi-tenant, and serverless architectures

  on AWS using services like

  SageMaker, Bedrock, Lambda, API Gateway, and OpenSearch.

• Work directly with the

  co-founders and leadership

  to influence AI/ML strategy and architecture decisions.

What You'll Do (Key Responsibilities)

First 30 Days: Foundation & Alignment

• Deep dive into

  goML's AI/ML & GenAI solution frameworks

  and ongoing client architectures.
• Familiarize yourself with

  AWS partnership workflows

  and solution templates.
• Partner with presales teams to

  understand client needs and pain points.

• Start designing and reviewing

  AI/ML workload deployment practices

  on AWS.

First 60 Days: Execution & Impact

• Own

  solution design and delivery

  for client AI/ML and LLM workloads.
• Build

  reference architectures, POCs

  , and define

  ML pipelines

  with MLOps best practices.
• Optimize

  inference, embeddings, GPU utilization, and cost efficiency

  across workloads.
• Collaborate with clients and internal teams to translate

  GenAI use cases into scalable architectures.

First 180 Days: Ownership & Leadership

• Lead

  architecture reviews

  for enterprise-grade AI/ML systems.
• Implement

  RAG pipelines

  , fine-tuning strategies, and

  LLM optimization frameworks.

• Mentor

  ML engineers and cloud developers

  in MLOps and scalable AI system design.
• Contribute to

  goML's AI/ML best practices

  , internal accelerators, and knowledge base.
• Represent goML in

  technical blogs, webinars, and community forums.

What You Bring (Qualifications & Skills)

Must-Have

• 67 years of experience

  in AI/ML solution design and deployment on AWS.
• Proven expertise in

  AWS AI/ML stack

  SageMaker, Bedrock, Lambda, ECS, API Gateway, S3, and DynamoDB.
• Experience in

  LLMOps, RAG pipelines, and GenAI architecture

  using models like Claude, Mistral, Llama, or Titan.
• Solid understanding of

  MLOps

  , CI/CD, and

  infrastructure automation

  (Terraform/CDK).
• Strong communication skills with experience in

  client-facing discussions

  and technical proposal creation.

Nice-to-Have

• Exposure to

  Azure ML, GCP Vertex AI, or NVIDIA AI/ML services.

• Hands-on experience with

  LangChain, Hugging Face

  , or

  vector databases

  (OpenSearch, Pinecone, FAISS).
• Familiarity with

  multi-cloud AI deployments

  and

  hybrid data architectures.

Why Work With Us

• Remote-first

  , with offices in Coimbatore for collaboration and innovation.
• Opportunity to

  build GenAI and AI/ML systems

  that power enterprise-scale transformations.
• Direct impact on

  technical strategy, solution architecture, and client success.