Staff Machine Learning Engineer
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.
Key Responsibilities
- Architect scalable and reliable AIML solutions that align with the company's tech paved path and stakeholder requirements.
- 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.
- 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.
- Debug and troubleshoot model performance issues, track key metrics, and continuously enhance model reliability, speed, and efficiency in production environments.
- Own the complete lifecycle of ML models, including monitoring, retraining, fine‑tuning and managing versions of models to ensure they continue to meet business needs over time.
- 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.
Qualifications
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.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.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 : evaluation 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 ideating, integrating, and designing applications and frontends using React or similar.Salary
$130,000.00 – $260,000.00 per annum (range is general; final offer may vary based on experience, location, etc.)
GEICO will consider sponsoring a qualified applicant for employment authorization for this position.
Equal Employment Opportunity
The equal employment opportunity policy of the GEICO Companies provides for a fair and equal employment opportunity for all associates and job applicants regardless of race, color, religious creed, national origin, ancestry, age, gender, pregnancy, sexual orientation, gender identity, marital status, familial status, disability or genetic information, in compliance with applicable federal, state and local law. GEICO hires and promotes individuals solely on the basis of their qualifications for the job to be filled.
GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and / or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates. GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment. We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants.
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