Full-Time

Machine Learning Lead

Confirmed live in the last 24 hours

Ema

Ema

51-200 employees

Develops enterprise AI solutions for workforce efficiency

Compensation Overview

$135k - $300k/yr

+ Variable Compensation + Equity

Senior, Expert

San Francisco, CA, USA

Employees are expected to work from the office three days a week.

Category
Natural Language Processing (NLP)
AI & Machine Learning
Required Skills
Microsoft Azure
Python
Tensorflow
Data Structures & Algorithms
Pytorch
SQL
Machine Learning
Natural Language Processing (NLP)
Reinforcement Learning
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.
Desired Qualifications
  • Experience with machine learning model lifecycle management tools, and an understanding of MLOps principles and best practices.

Ema develops and implements AI solutions specifically designed for businesses. Their main product is AI employees that can be customized through conversation to learn and perform tasks that exceed human capabilities, effectively increasing workforce productivity in a short time. Ema's technology replaces traditional co-pilots with secure and compliant AI employees, following 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 operations. The company's goal is to help enterprises achieve exceptional efficiency through advanced AI solutions offered on a subscription or licensing basis.

Company Size

51-200

Company Stage

Series A

Total Funding

$61M

Headquarters

Mountain View, California

Founded

2023

Simplify Jobs

Simplify's Take

What believers are saying

  • Ema's partnership with KPMG and Hitachi advances enterprise AI solutions.
  • Ema's customer base has more than doubled since its launch in March.
  • Ema's AI solutions are gaining traction in fintech, legal, healthcare, and e-commerce sectors.

What critics are saying

  • Emerging competition from startups like Galileo could challenge Ema's market position.
  • Rapid AI development may lead to potential obsolescence of Ema's current models.
  • Reliance on partnerships with large corporations could pose a risk if they fail.

What makes Ema unique

  • EmaFusionTM integrates over 100 LLMs for high accuracy and low cost.
  • Ema offers secure, compliant AI employees adhering to SOC2, ISO27001, GDPR, HIPAA, and NIST.
  • Ema's AI employees can be conversationally built to perform tasks beyond human capabilities.

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Benefits

Hybrid Work Options

Growth & Insights and Company News

Headcount

6 month growth

4%

1 year growth

1%

2 year growth

62%
Aibase
Apr 27th, 2025
Ema Unveils New Language Model, EmaFusion: Outperforming O3, Gemini in Cost and Accuracy

| Ema is partnering with global leaders like KPMG and Hitachi to advance enterprise AI.

VentureBeat
Jan 23rd, 2025
Galileo Launches ‘Agentic Evaluations’ To Fix Ai Agent Errors Before They Cost You

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. Galileo, a San Francisco-based startup, is betting that the future of artificial intelligence depends on trust. Today, the company launched a new product, Agentic Evaluations, to address a growing challenge in the world of AI: making sure the increasingly complex systems known as AI agents actually work as intended.AI agents—autonomous systems that perform multi-step tasks like generating reports or analyzing customer data—are gaining traction across industries. But their rapid adoption raises a crucial question: How can companies verify these systems remain reliable after deployment? Galileo’s CEO, Vikram Chatterji, believes his company has found the answer.“Over the last six to eight months, we started to see some of our customers trying to adopt agentic systems,” said Chatterji in an interview. “Now LLMs can be used as a smart router to pick and choose the right API calls towards actually completing a task

Leiphone
Aug 2nd, 2024
Ema secures $50M in Series A funding

Ema, a generative AI company, has secured $50 million in Series A funding, led by Accel and Section 32, with participation from Prosus Ventures, Sozo Ventures, Hitachi Ventures, Wipro Ventures, SCB 10X, Colle Capital, and Frontier Ventures. This brings Ema's total funding to $61 million. Since its launch in March, Ema's customer base has more than doubled.

Finsmes
Aug 1st, 2024
Ema Adds $36M to Series A Funding

Ema, a San Francisco, CA-based generative AI company creating the universal employee of the future, added $36M to its Series A funding which now totals $50M.

VentureBeat
Jul 31st, 2024
Ema raises $36M to build universal AI employees for enterprises

Ema raises $36M to build universal AI employees for enterprises.