ML Platform Lead: AWS/Databricks & LLM Solutions

Cyberobotix; Atlanta (GA); Hybrid; USD 170,000 - 260,000; Full time

Job summary

Cyberbotix is seeking an ML Lead to design and run a scalable ML platform on AWS and Databricks, owning the full lifecycle from design to production support. You will coach an offshore team and serve as the primary technical contact for client stakeholders.

The role emphasizes building agentic AI solutions, governance, cost optimization, and talent development, with a fixed hybrid schedule and a requirement for 12+ years experience.

Qualifications

• 8+ years in data science, ML engineering, or data engineering.
• 3+ years leading teams or technical delivery.
• Strong hands-on experience with Databricks (Spark, Delta Lake, MLflow, Unity Catalog, Workflows, Model Serving, Feature Store).
• Strong hands-on experience with AWS (S3, IAM, VPC, SageMaker, Lambda, ECS/EKS, Bedrock, CloudWatch, Glue).
• Proven experience building and operating production ML systems, not only prototypes.
• Experience delivering LLM and agentic applications (LangChain, LangGraph, LlamaIndex, Databricks Mosaic AI Agent Framework, or Bedrock Agents), including vector search and RAG.
• Proficiency in Python and SQL; solid software engineering practices (Git, testing, CI/CD, IaC such as Terraform).
• Experience leading distributed or offshore teams and coaching engineers.
• Strong client-facing skills, with the ability to explain complex topics to non-technical stakeholders.
• Experience with production support models, including SLAs, incident management, and monitoring.

Responsibilities

• Design, build, and evolve a scalable, secure ML platform on AWS and Databricks, covering feature engineering, training, experiment tracking, model registry, deployment, and monitoring.
• Establish MLOps standards: CI/CD for models and pipelines, infrastructure as code, automated testing, model versioning, and reproducibility.
• Implement governance with Unity Catalog, including access control, lineage, and auditability.
• Optimize platform cost, performance, and reliability (cluster policies, autoscaling, FinOps practices).
• Lead the design and delivery of ML use cases such as forecasting, classification, recommendation, and personalization.
• Architect and deliver agentic AI solutions: LLM-based agents, RAG pipelines, tool and function calling, multi-step orchestration, and evaluation frameworks.
• Define guardrails for LLM applications, including prompt management, hallucination and safety evaluation, observability, and cost controls.
• Evaluate new frameworks and models, and make build-versus-buy recommendations.
• Own end-to-end product delivery: roadmap, estimation, sprint planning, release management, and quality.
• Own production support: incident response, root cause analysis, SLAs, runbooks, on-call rotation, and model performance and drift monitoring.
• Balance feature delivery against operational stability and technical debt.
• Lead, mentor, and upskill an offshore team of ML engineers and data engineers.
• Set coding, review, and documentation standards, and run design and code reviews.
• Provide clear task breakdowns and ensure effective handoffs across time zones.
• Build team capability in MLOps, LLM engineering, and platform best practices.
• Act as the technical lead with clients: gather requirements, translate business problems into ML solutions, and manage expectations.
• Present architecture, progress, risks, and outcomes to technical and executive audiences.
• Partner with product, data engineering, security, and architecture teams.

Job description

Cyberbotix is seeking an ML Lead to design and run a scalable ML platform on AWS and Databricks, owning the full lifecycle from design to production support. You will coach an offshore team and serve as the primary technical contact for client stakeholders.

The role emphasizes building agentic AI solutions, governance, cost optimization, and talent development, with a fixed hybrid schedule and a requirement for 12+ years experience.