Ema Unlimited Logo

Ema Unlimited

Software Engineering Lead, Machine Learning

Reposted One Month Ago
In-Office or Remote
6 Locations
135K-300K Annually
Senior level
In-Office or Remote
6 Locations
135K-300K Annually
Senior level
Lead the development and deployment of advanced machine learning models focusing on NLP, while ensuring model integrity and communication with stakeholders.
The summary above was generated by AI
About Ema

Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs.

We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale.

Who you are

We're looking for an innovative and passionate Machine Learning Engineers to join our team. You are someone who loves solving complex problems, enjoys the challenges of working with huge data sets, and has a knack for turning theoretical concepts into practical, scalable solutions. You are a strong team player but also thrive in autonomous environments where your ideas can make a significant impact. You love utilizing machine learning techniques to push the boundaries of what is possible within the realm of Natural Language Processing, Information Retrieval and related Machine Learning technologies. Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact.

You will:
  1. Conceptualize, develop, and deploy machine learning models that underpin our NLP, retrieval, ranking, reasoning, dialog and code-generation systems.

  2. 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.

  3. 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.

  4. Work across the complete lifecycle of ML model development, including problem definition, data exploration, feature engineering, model training, validation, and deployment.

  5. 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.

  6. Clearly communicate the technical workings and benefits of ML models to both technical and non-technical stakeholders, facilitating understanding and adoption.

Ideally, you'd have:
  1. A Master’s degree or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.

  2. Proven industry experience in building and deploying production-level machine learning models.

  3. Deep understanding and practical experience with NLP techniques and frameworks, including training and inference of large language models.

  4. Deep understanding of any of retrieval, ranking, reinforcement learning, and agent-based systems and experience in how to build them for large systems.

  5. Proficiency in Python and experience with ML libraries such as TensorFlow or PyTorch.

  6. Excellent skills in data processing (SQL, ETL, data warehousing) and experience working with large-scale data systems.

  7. Experience with machine learning model lifecycle management tools, and an understanding of MLOps principles and best practices.

  8. Familiarity with cloud platforms like GCP or Azure.

  9. Familiarity with the latest industry and academic trends in machine learning and AI, and the ability to apply this knowledge to practical projects.

  10. Good understanding of software development principles, data structures, and algorithms.

  11. Excellent problem-solving skills, attention to detail, and a strong capacity for logical thinking.

  12. The ability to work collaboratively in an extremely fast-paced, startup environment.

For California based candidates:
The standard base salary for this position is $200,000-$270,000 annually.

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.

Ema Unlimited is an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or genetics.

Ema Unlimited San Francisco, California, USA Office

San Francisco, California, United States

Similar Jobs

3 Hours Ago
In-Office or Remote
7 Locations
136K-245K Annually
Senior level
136K-245K Annually
Senior level
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
Develop and manage Square’s always-on B2B content engine across social, thought leadership, customer stories, partner content, and industry narratives. Build content calendars, formats, briefs, campaigns, and AI-assisted workflows; collaborate with marketing, sales, creative, communications, and external partners; manage production through launch; and use performance insights to optimize content and distribution.
Top Skills: Ai ToolsLinkedInSocial Media Platforms
Yesterday
Easy Apply
Remote or Hybrid
Easy Apply
143K-185K Annually
Senior level
143K-185K Annually
Senior level
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Leads Samsara’s globally distributed Core Infrastructure team, owning strategy and roadmaps across compute, networking, storage, cloud systems, reliability, and operational efficiency. Responsibilities include developing engineers, improving capacity management and observability, strengthening incident response and disaster recovery, building automation and self-service infrastructure, and applying AI-enabled tools to reduce toil. The role requires significant software engineering and people-management experience, strong technical judgment, and expertise in large-scale cloud or distributed platforms.
Top Skills: Ai-Enabled Engineering ToolsCloud PlatformsContainer OrchestrationDeclarative InfrastructureDistributed SystemsObservability
Yesterday
Remote
80K-84K Annually
Entry level
80K-84K Annually
Entry level
Artificial Intelligence • Software
Own the full sales cycle for net-new SMB accounts in Canada, from prospecting through negotiation and close. Build relationships with CPA, audit, advisory, and assurance firms; conduct discovery; present Fieldguide’s AI audit platform; develop territory and account plans; apply MEDDICC; maintain CRM accuracy and forecasts; collaborate cross-functionally; and attend networking events. The role requires achieving sales targets and involves up to 30% regional and national travel.
Top Skills: AICRM

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account