[Hiring] Senior Machine Learning Engineer @phData

Role Description

We are looking for a Senior Machine Learning Engineer to join our Applied AI team. In this role, you will design, build, and operationalize production-ready AI and machine learning systems that solve meaningful business problems for enterprise customers. You will help move solutions from experimentation into scalable production, while contributing to reusable accelerators and engineering standards. You will collaborate closely with Applied AI Solutions Architects, data scientists, data engineers, platform engineers, project stakeholders, and client representatives to deliver high-quality solutions and advance phData's delivery excellence.

Key Responsibilities

• Build and operationalize production-ready Applied AI and machine learning solutions that align with customer objectives, technical requirements, and enterprise environments.
• Translate solution architectures and business requirements into clean, maintainable, well-tested code, data and model pipelines, and technical deliverables for AI applications.
• Implement robust production patterns for predictive ML, generative AI, LLM applications, agentic workflows, and intelligent automation, including evaluation, monitoring, and guardrails.
• Integrate AI solutions with enterprise data platforms, applications, APIs, and workflows, ensuring reliability, security, performance, and cost-effectiveness in production.
• Contribute to reusable accelerators, reference implementations, engineering standards, and technical playbooks that improve how phData delivers Applied AI solutions across clients.

Qualifications

• 5+ years of experience in AI/ML engineering, software engineering, data engineering, or a related technical discipline, including at least 3 years designing, building, deploying, or operating AI and machine learning solutions in production.
• Strong programming experience in Python for building production-grade AI, ML, and data pipelines.
• Strong working knowledge of SQL for querying, transforming, and validating data used in AI and ML solutions.
• Practical experience with modern cloud, data, and AI ecosystems such as Snowflake, Databricks, AWS, Azure, Google Cloud, dbt, Anthropic, OpenAI, or comparable technologies.
• Understanding of production AI/ML concerns, including evaluation, observability, security, governance, scalability, performance, and operational support.
• Experience developing production software, APIs, services, data pipelines, or AI applications and integrating them into enterprise environments.
• Bachelor's degree in relevant field, or equivalent practical experience (if desired).

Preferred Qualifications

• Experience building agentic AI systems, including orchestration, tool use, planning, memory, multi-agent patterns, or protocols such as MCP.
• Experience designing and deploying enterprise RAG systems, semantic retrieval, AI applications, or intelligent workflow automation.
• Experience with cloud-native AI/ML services such as AWS Bedrock and SageMaker, Azure AI/ML, Google Vertex AI, or Snowflake Cortex, and with LLM orchestration frameworks such as LangChain or LlamaIndex.
• Experience with model registries, feature stores, data and model lineage, model monitoring, drift detection, AI evaluations, prompt management, AI gateways, and CI/CD for AI/ML workloads.
• Experience building reusable accelerators, modular architectures, or libraries deployed across multiple clients, and contributions to open-source projects or technical communities.

Benefits

• Remote-First Work Environment
• Casual, award-winning small-business work environment
• Collaborative culture that prizes autonomy, creativity, and transparency
• Competitive compensation, excellent benefits, generous PTO plan plus 10 Holidays (and other cool perks)
• Accelerated learning and professional development through advanced training and certifications