NEWPosted 3 hours ago

Job ID: JOB_ID_3389

Role: ML Ops Engineer

We are looking for a skilled ML Ops Engineer with hands-on experience in Dataiku and SageMaker to join our team. This role is pivotal in designing, building, and maintaining robust MLOps pipelines for our advanced AI/ML initiatives.

Key Responsibilities:

  • Design Multi-Agent Architectures: Define agent roles (planner, researcher, executor, reviewer), toolboxes, handoffs, memory strategy (short/long-term), and supervisor policies for safe collaboration.
  • Build High-Quality RAG: Implement ingestion, chunking, embeddings, indexing, and retrieval with evaluation (precision/recall, groundedness, hallucination checks), guardrails, and citations.
  • Productionize on AWS: Leverage services such as Bedrock (Agents/Knowledge Bases/Flows), Lambda, API Gateway, S3, DynamoDB, OpenSearch/Vector DB, Step Functions, and CloudWatch for tracing and alerts.
  • MLOps/LLMOps: Automate CI/CD (GitOps), containerization (Docker/Kubernetes), infra-as-code, secrets/IAM, blue-green deployments/rollbacks, and data/feature pipelines.
  • Observability & Evaluation: Instrument telemetry (traces, token/cost, latency), build dashboards (Grafana/CloudWatch), add human-in-the-loop review, A/B testing, and continuous offline/online evaluations.
  • Operate Reliably at Scale: Implement caching, rate-limit management, queueing, idempotency, and backoff; proactively detect drift and degradation.
  • Collaborate & Communicate: Partner with infra/DevOps/data/architecture teams; document designs, SLIs/SLOs, runbooks; present status and insights to technical and non-technical stakeholders.

Minimum Qualifications:

  • Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field, or equivalent experience.
  • Proven experience building agentic systems (single or multi-agent) and RAG pipelines in production.
  • Strong cloud background for AI/ML workloads; familiarity with Bedrock or equivalent LLM platforms.
  • Solid CI/CD and containerization skills (Git, Docker, Kubernetes) and infra-as-code fundamentals.
  • Knowledge of data governance and model accountability throughout the MLOps/LLMOps lifecycle.
  • Excellent communication, collaboration, and problem-solving skills; ability to work independently and within cross-functional teams.
  • Passion for Generative AI and the impact of agent-based solutions across industries.

Preferred/Good to Have Qualifications:

  • Experience with AWS Bedrock Agents/Knowledge Bases/Flows, OpenSearch (or other vector databases), Step Functions, Lambda, API Gateway, DynamoDB, S3.
  • Dataiku platform exposure (govern, approvals, artifacts, MLOps deployment flows); SageMaker for custom model hosting.
  • Familiarity with agent frameworks (e.g., LangGraph, crewAI, Semantic Kernel, AutoGen) and evaluation frameworks (guardrails, groundedness, hallucination checks).
  • Covered Dataiku Certifications (nice to have): ML Practitioner, Advanced Designer, MLOps Practitioner.

Compensation & Location

Salary: $110,000 – $160,000 per year (Estimated)

Location: Reading, PA

Recruiter / Company – Contact Information

Email: h.k@voltoconsulting.com

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