Senior Machine Learning Engineer
Actively Hiring
Full-time Posted 10 months ago
Role overview
- check_circle Design, train, and fine-tune LLMs and domain-specific NLP models for text understanding, summarization, and retrieval tasks
- check_circle Develop scalable data pipelines, embeddings, and vector search systems for unstructured construction data
- check_circle Integrate RAG (Retrieval-Augmented Generation) systems into production applications
- check_circle Collaborate cross-functionally with product and platform teams to deliver ML-driven product features end-to-end
- check_circle Evaluate and optimize model performance for latency, accuracy, and robustness in production environments
Basic qualifications
- 4+ years of professional industry experience, with at least 2 years focused on NLP
- Proven experience training and fine-tuning LLMs and transformer-based architectures (e.g., GPT, BERT, T5, LLaMA)
- Proficiency in NLP frameworks and libraries such as Hugging Face Transformers, spaCy, PyTorch, TensorFlow, LangChain, and OpenAI APIs
- Experience with search and retrieval technologies including Elasticsearch, Pinecone, Milvus, Weaviate, FAISS, or Vespa
- Familiarity with RAG architectures and building context-aware AI systems
- Strong programming skills in Python and experience deploying ML models in cloud environments (AWS, GCP, or Azure)
- Prior experience in startups or small, fast-paced teams with ownership of full product lifecycles
Benefits
- check_circle Competitive cash compensation and meaningful equity stake
- check_circle Health, dental, and vision insurance coverage
- check_circle Flexible hybrid and remote work options
- check_circle Unlimited PTO
Tags & Focus Areas
Ai Machine Learning Nlp Generative Ai Pytorch Tensorflow Fulltime
About Harnham
Note: The job is a remote job and is open to candidates in USA. Harnham is a fast-growing AI company transforming one of the world’s largest and most operationally complex industries through intelligent automation. They are seeking an NLP Engineer to build and enhance search and retrieval systems, process multi-format documents, and develop domain-specific language models.