Software Engineer, Machine Learning
$160k - $220k • Remote • San Francisco Bay Area • FullTime
Posted 1y ago
Job Location
San Francisco Bay Area
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Machine Learning Engineer
About the job
Ema builds AI Employees for HR, IT, and Finance, automating busy work across the employee experience. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team comprises engineers from premier tech companies and graduates of top universities. We are backed by leading investors and are at the forefront of Agentic AI, shipping real systems that run business processes at scale. We are seeking innovative and passionate Machine Learning Engineers who excel at solving complex problems with large datasets, transforming theoretical concepts into practical, scalable solutions, and pushing the boundaries of Natural Language Processing and Information Retrieval.
Responsibilities
- Conceptualize, develop, and deploy machine learning models for NLP, retrieval, ranking, reasoning, dialog, and code-generation systems.
- Implement advanced machine learning algorithms like Transformer-based models, reinforcement learning, ensemble learning, and agent-based systems.
- Process and analyze large, complex datasets to inform model development.
- Manage the complete lifecycle of ML model development, from problem definition to deployment.
- Implement A/B testing and statistical methods to validate model effectiveness and ensure robustness through automated testing.
- Communicate technical workings and benefits of ML models to both 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 understanding and practical experience with NLP techniques and frameworks, including training and inference of large language models.
- Deep understanding of retrieval, ranking, reinforcement learning, and/or agent-based systems and experience building them for large systems.
- Proficiency in Python and experience with ML libraries such as TensorFlow or PyTorch.
- Excellent skills in data processing (SQL, ETL, data warehousing) and experience with large-scale data systems.
- Experience with machine learning model lifecycle management tools and MLOps principles.
- Familiarity with cloud platforms like GCP or Azure.
- Familiarity with the latest industry and academic trends in machine learning and AI.
- Good understanding of software development principles, data structures, and algorithms.
- Excellent problem-solving skills, attention to detail, and logical thinking.
- Ability to work collaboratively in a fast-paced startup environment.
Benefits
- Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience.
- Certain roles may be eligible for variable compensation, equity, and benefits.