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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer II - **Company:** GEICO - **Location:** New York, NY, United States - **Experience:** Experienced - **Salary:** $105,000.0 - $215,000.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Java (Programming Language), Artificial Intelligence, Amazon Web Services, Automation of Tests, Microsoft Azure, Big Data, Continuous Delivery, Extract Transform Load (ETL), Software Debugging, Software Design Patterns, Distributed Systems, Fault Tolerance, Python (Programming Language), Machine Learning, Object-Oriented Software Development, Open Source Technology, Performance Tuning, Systems Development Life Cycle, Tensorflow, Software Deployment, Software Engineering, SQL Databases, Systems Architecture, Systems Integration, Workflow Management Systems, Scripting, Google Cloud, Pytorch, ReactJS, System Availability, Delivery Pipeline, Large Language Models, Prompt Engineering, Apache Spark, Model Validation, Containerization, Scikit Learn, Kubernetes, Information Technology, Machine Learning Operations, Virtual Agents, Artificial Intelligence Markup Language (AIML), GPT, Docker - **Published:** May 30, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=0ccd38d8e3aeaa20 ## About the Role Do you have experience in System performance optimization?, Do you have a Bachelor's degree?, * Bachelor's degree in Machine Learning, Computer Science, Statistics, Mathematics, or a related field; an advanced degree (master's or Ph.D.) is highly desirable * At least 6 years of hands-on experience in machine learning and software engineering. * Technical Skills: * Deep proficiency in programming languages such as Python, Java, or similar, with a strong emphasis on coding excellence. * Proficiency in AIML frameworks such as TensorFlow, PyTorch, Scikit-learn, Langchain, langraph, etc. * Experience with SQL, Spark, and scripting languages such as Python for data processing and model development. * Expertise in cloud platforms (AWS, Azure, GCP) and containerization technologies such as Docker, as well as orchestration tools like Kubernetes. * Proven experience in deploying machine learning systems in a production environment, ensuring scalability, reliability, and high availability. * Core Engineering Skills: * Extensive experience with object-oriented design (OOD), design patterns, and writing clean, maintainable code. * Solid understanding of distributed systems and the challenges associated with scaling machine learning models in production. * Expertise in implementing MLOps practices, including setting up continuous integration (CI), continuous delivery (CD), automated testing, and deployment pipelines for machine learning models. * Strong understanding of system architecture, performance optimization, and the ability to design fault-tolerant systems that handle large-scale data and high-volume requests. * Experience designing, building, and maintaining ETL pipelines, streamlining data collection, transformation, and storage for model development. * Proficient in containerizing applications using Docker and managing deployment and scaling using Kubernetes or similar orchestrators. * Experience setting up monitoring and logging systems for tracking model performance in production environments and ensuring efficient resource utilization. Preferred Qualifications: * 3 years interfacing directly with internal business stakeholders and/or external stakeholders on AIML initiatives * Working experience with cloud provider solutions such as Azure and AWS * Experience utilizing both open source (e.g. llama, Qwen, Mistral) and proprietary (e.g. GPT, Claude) LLMs for appropriate tasks * Experience with tools that power LLM-based AI agents: eval frameworks, agent tooling, RAG pipelines, prompt engineering, etc. * Experience building LLM-based AI agent workflows via both no code/low code and traditional high-code development environments * Experience in ideating, integrating, and designing applications and frontends using React or similar. If you are passionate about pushing the boundaries of machine learning technology, thrive in a hands-on technical leadership role, and enjoy solving complex, large-scale problems, we encourage you to apply. ## Description Overview: As a Staff Machine Learning Engineer, you will be the overall tech lead of a single AI/Machine Learning team, responsible for the tech design and tech health of the team. You will build and architect scalable and reliable AIML solutions that align with the company's tech paved path and stakeholder requirements. This role requires a minimum of 6 years of relevant experience., System development: Architect scalable and reliable AIML solutions that align with the company's tech paved path and stakeholder requirements. Establish ML Best Practice: Develop and implement Software Development Lifecycle (SDLC) best practices for machine learning projects, ensuring scalable, secure, and reliable systems from model development to production deployment. Expected to stay hands-on coding about 70% of the time. Product Leadership & Feature Backlogs: Define the product roadmap for machine learning solutions and establish feature backlogs. Prioritize key ML features in collaboration with product managers, aligning them with business objectives and technical feasibility. Optimize Model Performance and Reliability Debug and troubleshoot model performance issues, track key metrics, and continuously enhance model reliability, speed, and efficiency in production environments. End-to-End Model Lifecycle Management: Own the complete lifecycle of ML models, including monitoring, retraining, finetuning and managing versions of models to ensure they continue to meet business needs over time. Leadership and Mentorship: Guide and mentor machine learning engineers, promote best practices in software engineering, model development, and deployment. Lead technical decision-making processes and foster collaboration within the team., Great Rewards: We offer compensation and benefits built to enhance your physical well-being, mental and emotional health and financial future. * Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family's overall well-being. * Financial benefits including market-competitive compensation; a 401K savings plan vested from day one that offers a 6% match; performance and recognition-based incentives; and tuition assistance. * Access to additional benefits like mental healthcare as well as fertility and adoption assistance. * Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year. ## Related Videos - [Watch Tests Go Brrrr! : Getting Started with Cypress in ReactJS](https://www.wearedevelopers.com/videos/282-watch-tests-go-brrrr-getting-started-with-cypress-in-reactjs) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Navigating the AI Revolution in Software Development](https://www.wearedevelopers.com/videos/1266-navigating-the-ai-revolution-in-software-development) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [How E.On productionizes its AI model & Implementation of Secure Generative AI.](https://www.wearedevelopers.com/videos/623-how-e-on-productionizes-its-ai-model-implementation-of-secure-generative-ai) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? 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