Full-Time

Machine Learning Engineer

SF Bay Area

Confirmed live in the last 24 hours

Ema

Ema

51-200 employees

Develops enterprise AI solutions for workforce efficiency

Cybersecurity
AI & Machine Learning

Mid

San Francisco, CA, USA

Hybrid role requiring in-office presence three days a week.

Category
Applied Machine Learning
Natural Language Processing (NLP)
AI & Machine Learning
Required Skills
Microsoft Azure
Python
Tensorflow
Data Structures & Algorithms
Pytorch
SQL
Natural Language Processing (NLP)
Google Cloud Platform
Requirements
  • A Master’s degree or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
  • Proven industry experience in 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 any of retrieval, ranking, reinforcement learning, and agent-based systems and experience in how to build 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 working with large-scale data systems.
  • Experience with machine learning model lifecycle management tools, and an understanding of MLOps principles and best practices.
  • Familiarity with cloud platforms like GCP or Azure.
  • Familiarity with the latest industry and academic trends in machine learning and AI, and the ability to apply this knowledge to practical projects.
  • Good understanding of software development principles, data structures, and algorithms.
  • Excellent problem-solving skills, attention to detail, and a strong capacity for logical thinking.
  • The ability to work collaboratively in an extremely fast-paced, startup environment.
Responsibilities
  • Conceptualize, develop, and deploy machine learning models that underpin our NLP, retrieval, ranking, reasoning, dialog and code-generation systems.
  • Implement advanced machine learning algorithms, such as Transformer-based models, reinforcement learning, ensemble learning, and agent-based systems to continually improve the performance of our AI systems.
  • Lead the processing and analysis of large, complex datasets (structured, semi-structured, and unstructured), and use your findings to inform the development of our models.
  • Work across the complete lifecycle of ML model development, including problem definition, data exploration, feature engineering, model training, validation, and deployment.
  • Implement A/B testing and other statistical methods to validate the effectiveness of models. Ensure the integrity and robustness of ML solutions by developing automated testing and validation processes.
  • Clearly communicate the technical workings and benefits of ML models to both technical and non-technical stakeholders, facilitating understanding and adoption.

Ema develops and implements AI solutions specifically designed for businesses. Their main product is AI employees, which can be customized through conversation to learn and perform tasks that exceed human capabilities, effectively increasing the workforce quickly. Ema's AI solutions replace traditional co-pilots with secure and compliant AI employees, meeting strict standards like SOC2, ISO27001, GDPR, HIPAA, and NIST. The EmaFusionTM model combines the strengths of over 100 large language models to deliver high accuracy at a low cost for various enterprise applications. Ema differentiates itself from competitors by focusing on compliance and security while providing tools that empower businesses to enhance their operational efficiency. The company's goal is to help enterprises gain control over their operations and achieve significant improvements in productivity through long-term partnerships.

Company Stage

Series A

Total Funding

$59.3M

Headquarters

Mountain View, California

Founded

2023

Growth & Insights
Headcount

6 month growth

60%

1 year growth

1666%

2 year growth

1666%
Simplify Jobs

Simplify's Take

What believers are saying

  • Securing $25 million in funding provides Ema with substantial resources to accelerate product development and market penetration.
  • The backing from prominent investors like Accel and Prosus Ventures enhances Ema's visibility and credibility in the competitive AI landscape.

What critics are saying

  • The enterprise AI market is highly competitive, with numerous well-funded players vying for market share.
  • Dependence on continuous innovation and high R&D expenditure could strain financial resources if market adoption is slower than anticipated.

What makes Ema unique

  • Ema focuses on enterprise-specific generative AI solutions, setting it apart from more generalized AI providers.
  • The company has attracted a diverse group of high-profile investors, including Accel, Section 32, and Prosus Ventures, which underscores its credibility and potential.

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