Alpha Talent Solutions - Joelle Borg

ML Engineer, LLM, Google Cloud

Alpha Talent Solutions - Joelle Borg

full-time

Posted on:

Location Type: Remote

Location: Remote • 🇺🇸 United States

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Job Level

Mid-LevelSenior

Tech Stack

AirflowCloudDockerGRPCKafkaKubernetesPythonPyTorchRabbitMQTensorflow

About the role

  • 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 competitive Salary along with quarterly bonuses
  • Opportunity to work on fully remote basis under a B2B Service Agreement

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
PythonMLNLPTensorFlowPyTorchHugging FaceMLOpsREST APIsDockerCI/CD
Soft skills
analytical skillsproblem-solvingcommunicationdocumentationcollaborationattention to detailorganizational skillsadaptabilitycreativitycritical thinking