Machine Learning Engineer

As a technical leader, you will guide engineers through design and implementation, contribute directly to the codebase, and lead architectural decisions across teams. Working primarily with Python and cloud-based data and AI platforms, with a growing emphasis on Databricks, you will shape the shared infrastructure supporting both established products and new AI applications. What You’ll Do

• Own technical delivery from prototype through deployment and ongoing production support, partnering with AI Scientists and Product to define requirements, plan implementation, and resolve cross-team dependencies.
• Evaluate proposed AI solutions for production suitability, identify technical risks, and choose architectures that meet quality, reliability, and cost requirements without unnecessary complexity.
• Architect and build high-volume AI services and processing pipelines, including fault tolerance, backpressure, retries, idempotency, and recovery from partial failures.
• Lead the evolution of our Python services and Databricks-based platform for distributed processing, model serving, and integration of traditional ML and LLM-based components.
• Establish production engineering standards for automated testing, CI/CD, model and prompt versioning, load testing, controlled rollouts, and rollback.
• Build evaluation and monitoring capabilities to detect AI quality regressions and track service reliability, throughput, latency, and inference cost.
• Partner with Product and Responsible AI teams to define release criteria and implement requirements for model validation, data privacy, security, and governance.
• Optimize processing and inference workloads, balancing model quality, throughput, latency, capacity, and cost.
• Mentor engineers and lead architecture and code reviews, maintaining consistent standards for software quality and maintainability.

• Bachelor’s degree in Computer Science, Electrical Engineering, or a related technical discipline, or equivalent practical experience.
• 8+ years of professional software engineering experience, including at least 3 years owning ML or LLM systems in production and their operational support.
• Proven track record of independently leading complex technical initiatives from requirements through production, making architectural decisions and coordinating delivery across stakeholders.
• Advanced proficiency in Python for production services and data processing, with strong SQL skills.
• Experience designing and operating high-throughput distributed systems, with a strong understanding of failure recovery, multi-tenancy, and capacity planning.
• Hands-on experience deploying and operating LLM-based applications, including evaluation, output validation, observability, and cost management.
• Strong production engineering practices across automated testing, CI/CD, monitoring, incident response, and root-cause analysis.
• Demonstrated technical leadership through system design, hands-on implementation, code review, and mentorship.
• Ability to communicate technical decisions and tradeoffs clearly to engineering, research, product, and governance stakeholders., * Experience with Databricks or comparable cloud-based data and AI platforms for workflow orchestration, scalable processing, model deployment, and evaluation.
• Experience with NLP, text analytics, or large-scale processing of unstructured data.
• Experience building shared infrastructure for inference, evaluation, and model lifecycle management.
• Familiarity with retrieval-augmented generation, semantic search, and LLM orchestration frameworks.
• Experience with speech-to-text, speaker diarization, or processing conversational audio data.
• Experience deploying and operating cloud-native services on AWS or Azure.
• Experience with healthcare or other regulated environments, including sensitive data handling, auditability, and model governance.

Lead the design, development, deployment, and operation of production AI and ML systems. Build high-throughput Python services and Databricks pipelines, support traditional ML and LLM applications, establish testing and deployment standards, and develop monitoring for quality, reliability, latency, throughput, and cost. Partner with product, research, and responsible AI teams on governance and release criteria. Provide architectural leadership, conduct code reviews, mentor engineers, and resolve complex technical dependencies. The summary above was generated by AI, The expected base salary for this position ranges from $130,000 to $190,000. It is not typical for offers to be made at or near the top of the range. Salary offers are based on a wide range of factors including relevant skills, training, experience, education, and, where applicable, licensure or certifications obtained. Market and organizational factors are also considered. In addition to base salary and a competitive benefits package, successful candidates are eligible to receive a discretionary bonus or commission tied to achieved results., Yesterday In-Office or Remote 277K-415K Annually Expert/Leader 277K-415K Annually Expert/Leader Blockchain * eCommerce * Fintech * Payments * Software * Financial Services * Cryptocurrency Lead end-to-end machine learning initiatives for Block’s conversational support systems. Responsibilities include developing and maintaining chatbot and recommendation models, researching LLM, RAG, fine-tuning, and real-time inference architectures, shaping long-term ML roadmaps, and guiding cross-functional teams. The role also requires communicating technical strategy and outcomes to leadership and external stakeholders while delivering scalable, production-ready AI solutions across Cash App, Square, and other Block products. Top Skills: Deep LearningJaxLarge Language Models (Llms)Natural Language Processing (Nlp)PythonPyTorchReal-Time InferenceRetrieval-Augmented Generation (Rag)TensorFlow, Cash App, 2 Days Ago Remote or Hybrid 277K-415K Annually Expert/Leader 277K-415K Annually Expert/Leader Blockchain * Fintech * Mobile * Payments * Software * Financial Services Leads end-to-end machine learning initiatives for Block’s support experiences, including conversational AI, chatbots, recommendation systems, and agent tools. Defines ML roadmaps, guides research into LLMs, RAG, fine-tuning, and real-time inference, and designs, deploys, and maintains production models. The role requires strategic technical leadership, cross-functional influence, stakeholder communication, and extensive experience delivering applied ML and generative AI systems. Top Skills: Deep LearningGenerative AiJaxLarge Language Models (Llms)Natural Language Processing (Nlp)PythonPyTorchReal-Time InferenceRetrieval-Augmented Generation (Rag)TensorFlow General Motors

Machine Learning Engineer

14 Days Ago Remote or Hybrid 219K-335K Annually Senior level 219K-335K Annually Senior level Automotive * Big Data * Information Technology * Robotics * Software * Transportation * Manufacturing Lead development of scalable, reliable continuous integration infrastructure supporting autonomous-vehicle development, machine learning training, simulation, and remote builds. Specialize in Remote Build Execution and a FUSE-based file system, enabling source-code editing and developer workflows. Design and implement productivity improvements, evaluate technologies, influence technical roadmaps, establish engineering best practices, manage technical debt, and mentor engineers while balancing business and customer priorities. Top Skills: DockerFuseGoGoogle Cloud Platform (Gcp)KubernetesNetworkingPythonRemote Build Execution (Rbe)SshUnix/Linux

What you need to know about the Colorado Tech Scene

With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.

Key Facts About Colorado Tech

• Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
• Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
• Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
• Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
• Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
• Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute

Press Ganey is the leading experience measurement, data analytics, and insights provider for complex industries-a status we earned over decades of deep partnership with clients to help them understand and meet the needs of their key stakeholders. Our earliest roots are in U.S. healthcare -perhaps the most complex of all industries. Today we serve clients around the globe in every industry to help them improve the Human Experiences at the heart of their business. We serve our clients through an unparalleled offering that combines technology, data, and expertise to enable them to pinpoint and prioritize opportunities, accelerate improvement efforts and build lifetime loyalty among their customers and employees.

Like all great companies, our success is a function of our people and our culture. Our employees have world-class talent, a collaborative work ethic, and a passion for the work that have earned us trusted advisor status among the world’s most recognized brands. As a member of the team, you will help us create value for our clients, you will make us better through your contribution to the work and your voice in the process. Ours is a path of learning and continuous improvement; team efforts chart the course for corporate success.

Our Mission:

We empower organizations to deliver the best experiences. With industry expertise and technology, we turn data into insights that drive innovation and action.

Our Values:

To put Human Experience at the heart of organizations so every person can be seen and understood.

• Energize the customer relationship: Our clients are our partners. We make their goals our own, working side by side to turn challenges into solutions.
• Success starts with me: Personal ownership fuels collective success. We each play our part and empower our teammates to do the same.
• Commit to learning: Every win is a springboard. Every hurdle is a lesson. We use each experience as an opportunity to grow.
• Dare to innovate: We challenge the status quo with creativity and innovation as our true north.
• Better together: We check our egos at the door. We work together, so we win together.