11 hours ago
Vancouver, CanadaMid Level
Responsibilities
- Conceptualize, develop, and deploy machine learning models for NLP, retrieval, ranking, reasoning, dialogue, and code-generation systems.
- Implement Transformer-based models, reinforcement learning, ensemble learning, and agent-based systems.
- Process and analyze large structured, semi-structured, and unstructured datasets to inform model development.
- Manage the full ML lifecycle, including problem definition, data exploration, feature engineering, training, validation, and deployment.
- Implement A/B testing, statistical validation, and automated testing processes for ML solutions.
- Explain ML model functionality and benefits to technical and non-technical stakeholders.
Requirements
- Master’s degree or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
- At least 2 years of industry experience building and deploying production-level machine learning models.
- Deep practical understanding of NLP techniques and frameworks, including training and inference of large language models.
- Experience with retrieval, ranking, reinforcement learning, or agent-based systems at large scale.
- Proficiency in Python and experience with TensorFlow or PyTorch.
- Preferred: SQL, ETL, data warehousing, large-scale data systems, ML lifecycle management tools, MLOps, GCP or Azure, software development principles, data structures, and algorithms.
Benefits
- Compensation is determined by location, level, job-related knowledge, skills, and experience.
- Certain roles may be eligible for variable compensation, equity, and benefits.
- The company has offices in Silicon Valley, London, Bangalore, and Vancouver; specific work arrangement is not stated.
Tech Stack
Categories
About Ema
Ema builds an agentic AI platform that delivers AI employees to automate HR, IT, and Finance workflows across existing enterprise systems. It sells to large organizations via enterprise software and implementation services, offering on-prem and air-gapped deployments and 1,000+ prebuilt integrations. Founded in 2023, it has deployments with Wipro and Hitachi.