Machine Learning Engineer (Agentic AI Platform) at Barker Staffing Solutions, LLC in Mountain View, California, United States

Job description

• We're building the next generation of agentic AI systems, intelligent, autonomous agents that reason, act, and continuously improve. As a Machine Learning Engineer, you won't just build models, you'll architect the entire ecosystem where our AI agents live, learn, and operate.
• This is a high-impact role for a product-minded, systems-level thinker who thrives in ambiguity and wants to shape foundational AI infrastructure from the ground up.
• You'll work at the intersection of LLMs, distributed systems, and real-world applications, owning everything from core ML architecture to customer-facing experiences.

Responsibilities

• Architect & Build Agentic Systems
• Design and develop our core agentic AI platform, enabling autonomous reasoning, decision-making, and continuous learning
• Implement multi-agent orchestration frameworks (e.g., LangGraph)
• Own the ML & Data Infrastructure
• Architect a modern lakehouse-based data platform
• Build scalable data pipelines, feature stores, and real-time ML serving systems
• Develop LLM-Powered Applications
• Build and optimize RAG systems, prompt pipelines, and reasoning workflows
• Develop customer-facing applications, including a seamless AI chat interface
• Build Tool Machines for Agents
• Create reliable, safe, and extensible tools that allow agents to interact with external systems, APIs, and data sources
• Drive MLOps & Model Lifecycle
• Partner with data scientists to design infrastructure for training, fine-tuning, evaluation, and deployment
• Implement robust experimentation, monitoring, and feedback loops
• Ship Production-Grade Systems
• Write high-quality, scalable Python code
• Ensure reliability, observability, and performance across distributed systems

Requirements

• 3–8 years of experience in Machine Learning Engineering or Software Engineering (ML-focused)
• Strong production experience with Python
• ML frameworks (e.g., PyTorch, TensorFlow)
• LLMs, agentic frameworks (e.g., LangGraph), or RAG systems
• Experience designing scalable ML systems (training + serving)
• Master's or PhD in Computer Science (or related field), OR
• Bachelor's degree + strong professional experience in software/ML engineering
• Experience at top-tier tech companies (e.g., Meta, Google, Reddit, Pinterest)
• Combined experience across Big Tech + high-growth startup environments
• Background in ads, search, recommendation systems, or large-scale ML platforms
• Prior experience at a venture-backed startup
• Kubernetes, MLflow, model serving systems
• Spark, Airflow, dbt, ETL/streaming pipelines
• Experience designing systems using lakehouse architectures

Skills

Required

• Python
• PyTorch
• TensorFlow
• LangGraph
• RAG architectures
• ML frameworks
• LLMs
• Agentic frameworks
• Scalable ML systems design
• Production experience

Preferred

• Kubernetes
• MLflow
• Model serving systems
• Spark
• Airflow
• dbt
• ETL/streaming pipelines
• Lakehouse architecture