Machine Learning Engineer

Job Title: Machine Learning Engineer Company: Hirivo Job Category: Machine Learning Roles & Responsibilities: You'll join a small applied\-AI team and own the ML behind Hirivo. That covers the job\-matching and ranking models, the LLM agents that read job adverts and fill application forms, and the systems that tell us whether they're working. You'll take features from prototype to production, then measure and monitor them. * Build and improve LLM\-powered agents that read job adverts and application forms and complete them accurately from a candidate's profile and CV (tool use, multi\-step workflows, handing questions to the candidate when needed). * Build job\-to\-candidate matching and ranking using embeddings, retrieval (RAG) and vector search, behind the campaign match score. * Create evaluation sets and automated evals for form\-fill accuracy, match quality and agent success rate, then iterate on prompts, models and fine\-tunes. * Train, fine\-tune and benchmark models (PyTorch), for example to parse CVs and job descriptions and to classify job fit. * Deploy models and agents as scalable APIs and services on the cloud (AWS/GCP) with Docker, Kubernetes and CI/CD, integrated with our Node backend. * Add observability: tracing of agent runs, latency/cost dashboards, failure and drift monitoring. * Build data pipelines that collect and clean job listings from many sources. * Work with product and with candidates to turn real job\-seeker problems into shipped features, and care about responsible AI: candidates' data, fairness and accuracy. * Building LLM evaluation frameworks (evals, benchmarks, LLM\-as\-judge). (40%)* * Monitoring and observability tooling (e.g. Datadog, OpenTelemetry, LangSmith). (55%)* * Open\-source contributions or a public portfolio of AI projects. (36%)* * A second language such as TypeScript, Go, C\+\+ or Rust. (TypeScript/JS 31%, Go 16%)* * GPU / CUDA / inference\-performance optimisation. (22%)* * Fine\-tuning (LoRA, RLHF/DPO). (18%)* * Familiarity with AI safety or responsible AI. (21%)* * Recommender/ranking systems, MLOps tooling (MLflow, model registry), web scraping/data pipelines. (13\-15% each)* Work Location: Hybrid remote in London Work Location: London, ENG, UK Availability: Full time

* Strong Python and solid software\-engineering fundamentals (APIs, backend services, testing). (Python appears in 64% of the sampled postings; APIs/backend in 54%.)* * Hands\-on experience building with LLMs: OpenAI/Anthropic APIs, prompting, agents or RAG. (LLMs 60%, agents 69%.)* * Experience shipping ML or AI systems to production and running them at scale. (Production 63%, scale 67%.)* * Experience training and evaluating models, plus familiarity with PyTorch. (Training/experimentation 48%.)* * Cloud experience (AWS, GCP or Azure) plus Docker/Kubernetes. (Cloud 40%.)* * A degree in Computer Science or a related field, or equivalent experience. * A product mindset: you care about users and measurable impact. (36%.)* Benefits: Key Skills: Machine Learning, Python, PyTorch Salary: GBP 35000 - 45000 per yearly