Senior Machine Learning Engineer

Summary

Join Laurel, a company on a mission to revolutionize how we measure and perform work by automating timekeeping. As a Senior Machine Learning Engineer, you will lead the development and implementation of machine learning models and services for our core product. You will collaborate with cross-functional teams, build and deploy scalable ML pipelines, and optimize workflows for efficiency. This role requires strong Python skills, experience with ML systems, and familiarity with various tools and technologies. The position offers a hybrid work model in LA, SF, or NY offices, or remote work on a case-by-case basis. Competitive compensation and comprehensive benefits are provided.

Requirements

• A developer with strong Python skills building and deploying machine learning models
• A ML systems thinker. Someone who can formulate a general product request into a machine learning problem and develop a clear document outlining the solution
• Experience with orchestration tools like Airflow
• Experience with AWS
• Familiarity with Git
• Experience with taking part in a regular engineering oncall rotation
• Experience with Pytorch or Tensorflow
• Experience with utilizing LLMs in a production system including RAG and fine-tuning
• Excellent communication skills

Responsibilities

• Leverage and customize pre-trained language models (e.g., GPT, BERT, LLama) to solve specific text-processing problems for downstream applications
• Develop and implement advanced text embedding techniques for tasks such as similarity search, clustering, and semantic understanding
• Integrate embeddings into scalable systems for personalization
• Lead the development of core NLP components like tokenization and named entity recognition
• Research and implement cutting-edge methods for text representation, generation, and augmentation
• Build and deploy end-to-end machine learning pipelines that scale efficiently in production environments
• Optimize training and inference workflows to minimize latency and maximize throughput on large datasets
• Preprocess and clean large text datasets to prepare them for machine learning tasks
• Engineer new features and data representations to enhance model performance
• Develop APIs and interfaces for seamless access to text models and embeddings
• Establish metrics to evaluate the performance of text-based ML systems (e.g., precision, recall, BLEU scores)
• Implement tools to monitor models in production for drift, performance degradation, and bias
• Collaborate with software engineers to integrate ML models into production systems, ensuring robustness, reliability, and maintainability
• Work closely with product managers, data scientists, and domain experts to align machine learning solutions with business goals
• Maintain clear and comprehensive documentation of ML models, data pipelines, and systems architecture
• Attend quarterly offsites (required travel), team standups, and other company meetings
• Participate in an on-call rotation

Preferred Qualifications

• Experience with PostgreSQL
• Experience with Django
• Experience building agents
• Experience with FastAPI

Benefits

• Comprehensive medical/dental/vision coverage
• 401(k)
• Commuter stipends
• Company offsites
• Unlimited sick leave
• Hybrid work model (3 days/week in office in LA, SF, or NY; remote considered on a case-by-case basis)