- Company Name
- Meltwater
- Job Title
- Machine Learning Engineer
- Job Description
-
**Job title:** Machine Learning Engineer
**Role Summary:**
Design, develop, and deploy large‑scale multimodal and generative AI features for an enterprise AI assistant. Own the end‑to‑end lifecycle of machine‑learning models—from prototyping and research to production, scalability, and monitoring—at a scale of billions of documents daily.
**Expectations:**
- Deep foundation in machine learning, data science, or applied research.
- Proven ability to translate experimentation into production‑grade systems.
- Strong engineering discipline: clean code, automated tests, CI/CD, and observability.
- Collaborative mindset; work closely with product and domain teams.
- Continuous learning of cutting‑edge ML advances and frameworks.
**Key Responsibilities:**
- Drive industrial‑scale ML projects from ideation through deployment.
- Prototype and research new algorithms, especially for multimodal and agentic reasoning.
- Build and maintain production‑grade pipelines, ensuring scalability, reliability, and monitoring.
- Design experiments, evaluation metrics, and validation strategies for large‑scale systems.
- Analyze model errors, bias, and failure modes to drive iterative improvements.
- Write efficient, well‑tested, maintainable code in Python/ML frameworks.
- Apply MLOps best practices (CI/CD, Terraform, Kubernetes, cloud services).
- Collaborate with product teams to translate business problems into ML solutions.
**Required Skills:**
- Machine learning fundamentals (supervised, unsupervised, reinforcement).
- Deep learning frameworks: PyTorch, TensorFlow, JAX.
- Experience with multimodal models (text, image, possibly audio).
- Large‑scale distributed training and inference (GPU/TPU, cloud).
- MLOps: CI/CD pipelines, Docker, Kubernetes, Terraform, cloud (AWS/GCP/Azure).
- Model monitoring, logging, and alerting.
- Strong programming in Python, version control (Git).
- SQL and data‑engineering fundamentals.
- Ability to write unit/integration tests and documentation.
- Knowledge of bias mitigation and explainability techniques.
**Required Education & Certifications:**
- Bachelor’s (or Master’s) degree in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or related field.
- PhD preferred for research‑heavy roles but not mandatory.
- No specific certifications required.
Redwood city, United states
Hybrid
23-02-2026