AI & Machine Learning Site Reliability Engineer

Responsibilities

• Big Data Analytics Platform Build and maintain Oomnitza’s big data analytics platform that centralizes data from multiple customer instances and serves analytics and AI solutions
• AI/ML Architecture & Infrastructure Development Design and build scalable, secure, and efficient AI infrastructure to support training and deploying machine learning models and AI software solutions.
• Vector Databases & Knowledge Graphs Implement and manage vector databases for storing high-dimensional data and knowledge graphs to integrate structured and unstructured data.
• Retrieval Augmented Generation (RAG) & GraphRAG Develop and integrate retrieval-augmented generation systems for more accurate, scalable, and context-aware models, including GraphRAG for advanced reasoning.
• LLM Fine-Tuning, Transfer Learning & Optimization Work with data scientists to train and optimize and fine-tune large language models (LLMs) for specific business applications and ensure seamless integration with existing systems.
• ML Model Deployment & Orchestration Deploy, manage, and monitor ML models in production, ensuring system reliability, scalability, and performance.
• CI/CD for Machine Learning Pipelines Implement continuous integration and continuous deployment (CI/CD) processes tailored for machine learning, ensuring reproducibility and automation.
• Agent Development & Automation Work with data scientists and the AI product management team todevelop and manage AI agents for task automation, process optimization, and adaptive learning systems.
• Model Monitoring & Governance Ensure model performance monitoring, retraining, and governance protocols are in place for reliable and ethical AI usage.
• Collaboration & Team Support Work closely with data scientists, ML engineers, and cross-functional teams to support development, testing, and deployment needs.

Qualifications

• Education: Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field 
• Experience: 5+ years of experience in site reliability engineering, dev ops, ML Ops or similar roleExperience with cloud platforms such as AWS, GCP, or Azure, including AI/ML services (e.g., SageMaker, Google Colab, Vertex AI).Proficient in deploying machine learning models such as regressions, decision trees, neural networks, recommendations systems, etc., into production and managing model lifecycle.
• Technical Skills: Experience with data processing tools such as Apache Spark, Hadoop, or Airflow for large-scale data processing.Experience with AI/ML tools and frameworks (e.g., TensorFlow, PyTorch, LangChain, Hugging Face).Strong understanding of vector databases (e.g., Pinecone, Milvus, Chroma) and knowledge graph tools (e.g., Neo4j, RDF).Experience with RAG (Retrieval-Augmented Generation) techniques and GraphRAG systems.Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).Proficiency in programming languages such as Python, Bash, and experience with ML tools and libraries.Experience implementing CI/CD for ML pipelines and working with ML version control systems (e.g., DVC, MLflow).Experience in on-call incident response in high-uptime environments
• Behavioural Skills: Intellectual curiosity with a hunger to know how things work and question established ideas, concepts and frameworks
• Spirit of service: with a “how can I serve” attitude that is centered around delivering value to the greater team, the overall company, and for our broader community of customers
• Ability to embrace ambiguity: and apply structured structured thinking and  problem-solving skills
• Entrepreneurial spirit with an enthusiasm to take on new challenges
• Excellent communication and collaboration skills

Additional (Preferred) Qualifications

• Master’s degree in a related field.
• Understanding of model governance, ethics, and AI risk management.
• Experience with private LLM fine-tuning and optimization.
• Familiarity with agent development for automation tasks.
• Experience with AI/ML deployment models directly on edge devices, such as smartphones, IoT devices, or embedded systems.
• Knowledge of advanced data infrastructure, including distributed systems and database design.

What We Can Offer You

• Healthcare for dependents and spouse 
• A progressive, healthy work culture with excellent opportunities for professional and personal development.  
• Top performers will have an opportunity to help shape the team. Working directly with the founders to drive initiatives and create a structure that scales.
• A once-in-a-lifetime career opportunity to get onboard a fast-growing business that is venture-backed by C5 Capital, Shasta Ventures, Riverside Acceleration Capital, and Hummer Winblad

Our Benefits Package

• Dental & Vision Insurance 
• Employee equity plan
• Health Insurance for your spouse and dependents 
• Pension, Life insurance and Income protection
• Remote working & flexible work schedules Working from home equipment allowance
• Choice of preferred equipment, Mac or PC.
• Regular, fun social events and  workshops.