ML Engineer, LLM, Google Cloud
Job Description:• Analyse business requirements for the desired output format and the logic the model must implement. • Prepare datasets based on example texts: cleaning, annotation, creating training/validation splits. • Train and fine-tune LLMs for specific use cases: configure training parameters; experiment with prompts, system instructions, input/output formats. • Evaluate model quality: design and track metrics; create test scenarios and A/B experiments; ensure output format consistency and stability.• Deploy models to Google Cloud (for example via Vertex AI, Cloud Run, Kubernetes, etc.). • Develop services and APIs (REST/gRPC) that expose the model to other systems. • Build automations and integrations that call the model: background jobs, queues, event-driven triggers; integration with internal services and databases. • Implement MLOps pipelines: automate training / retraining workflows; version models and datasets; monitor model performance and quality in production. • Document models, pipelines, APIs, and architectural decisions.Requirements:• 3+ years of software development experience (preferably Python)• Hands-on experience with ML / NLP: understanding of models, loss functions, training and validation workflows• Practical experience with at least one ML framework: TensorFlow, PyTorch, Hugging Face, etc. • Experience with Google Cloud: Core services (Cloud Storage, IAM, VPC); ideally Vertex AI, Cloud Run, Pub/Sub or similar• Experience deploying models into production (API services, containerization with Docker, CI/CD)• Experience building and integrating REST APIs; confident working with JSON/JSONL, logging, and monitoring• Understanding of how to design reliable and scalable systems (error handling, retries, queues, timeouts)• Direct experience with LLMs: prompt engineering, few-shot learning, RAG• Experience with MLOps tools (MLflow, Vertex AI Pipelines or equivalents)• Experience with messaging/queue systems (Pub/Sub, Kafka, RabbitMQ) and workflow orchestration (Workflows, Airflow, etc.)• Understanding of data security and handling sensitive information, including access control (IAM)Benefits:• Highly competitiveSalary along with quarterly bonuses• Opportunity to work on fully remote basis under a B2B Service Agreement Apply tot his job