About the Role

As a Senior Machine Learning Engineer, you will lead efforts to build models and services that support our core timekeeping product. You’ll collaborate closely with cross-functional teams to design and deploy cutting-edge machine learning to support core product features. Beyond developing models, you’ll build and shape our engineering services that support training and deploying models.

Responsibilities

Machine Learning and Language Models:

• 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.

Engineering:

• 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.

Cross-Functional Collaboration and Communication:

• 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.

Other engineering duties:

• Attend quarterly offsites (required travel), team standups, and other company meetings.
• Participate in an on-call rotation.

What We're Looking For

The following are our non-negotiables for candidates.

• 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

Nice to haves

The following are things that we are looking for in a standout candidate and would help make this role a perfect fit.

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

Flexibility and Logistics:

• Location: This role will be hybrid in our LA, SF, or NY offices 3 days per week; we may consider Remote US candidates on a case-by-case basis.
• Additional Benefits: Comprehensive medical/dental/vision coverage, 401(k), and additional benefits including commuter stipends, and company offsites.
• Compensation: For candidates based in NY, SF or LA, the compensation range for this role is $160,000-$210,000 USD. Final compensation amounts will be determined based on several factors including candidate experience, technical qualifications and expertise and may vary from the amounts listed.
• Visa Sponsorship: Unfortunately we are unable to sponsor visas at this time.
• What happens if my kid or I are sick on a workday? Take all the time you need! We’ll cover for you. And send you some soup.

#LI-Remote