- Company Name
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- Job Title
- Associate AI/ML Developer
- Job Description
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Job Title: Associate AI/ML Developer
Role Summary:
Support the development and operation of a cloud‑native AI/ML platform that enables self‑service pipelines, model governance, and GenAI workloads for enterprise applications.
Expectations:
- Deliver scalable, reliable, and secure AI/ML services in a hybrid cloud environment.
- Strengthen developer productivity through reusable tooling, templates, and best‑practice patterns.
- Apply observability, monitoring, and governance practices to protect and optimize large‑language‑model deployments.
Key Responsibilities:
* Build and maintain Python‑based services and frameworks deployed on GKE using GitOps (ArgoCD, GitHub Actions).
* Design and extend AI/ML pipeline components with Composer (Airflow), Vertex AI, Dataflow, Dataproc, and BigQuery.
* Implement GenAI patterns (RAG, vector stores, agentic frameworks) and provide reusable components via LangChain/LangGraph/CrewAI/Autogen.
* Integrate monitoring, evaluation, and guardrails (Arize, LangSmith, LiteLLM, etc.) to enforce LLM governance, safety, and cost management.
* Collaborate with infrastructure and security teams to embed enterprise security tooling (NexusIQ, StackRox, Wiz) and RBAC controls into ML workflows.
* Troubleshoot, debug, and improve reliability of production AI/ML workloads, implementing logging, alerting, and SLOs (Splunk, New Relic, PagerDuty).
* Participate in incident response, root‑cause analysis, and continuous platform improvement.
Required Skills:
* 2+ years of cloud‑native software engineering experience.
* Strong proficiency in Python (object‑oriented).
* Hands‑on experience with GCP (Vertex AI, GKE, BigQuery, Composer/Airflow, Dataflow, Dataproc) or equivalent cloud provider.
* Knowledge of GenAI concepts: RAG, vector embeddings, prompt management, evaluation, agent frameworks.
* Expertise in Kubernetes, Docker, and containerized deployments.
* Familiarity with GitOps/CI‑CD pipelines (ArgoCD, GitHub Actions).
* Experience with production support: debugging, monitoring, incident response.
* Familiarity with MLOps tools, security best practices, and SRE concepts is a plus.
Required Education & Certifications:
* Bachelor’s degree (or higher) in Computer Science, Engineering, or a related technical field (or equivalent practical experience).