Machine Learning Engineer, Contextual AI
$150-250k
+ Equity
Office located in Mountain View, CA
Contextual language models for enterprise
Open for applications
Contextual language models for enterprise
21-100 employees
Open for applications
$150-250k
+ Equity
Office located in Mountain View, CA
21-100 employees
Company mission
To change the way the world works through AI.
Role
Who you are
- Educational Background: Bachelor's degree in computer science, engineering, mathematics, statistics, or a related field. Master’s or Ph.D. preferred
- Technical Proficiency: Proficiency in Python and experience with popular machine learning tools (e.g., PyTorch, TensorFlow, scikit-learn, HuggingFace)
- Machine Learning Expertise: Strong understanding of machine learning, deep learning (including LLMs), and natural language processing, with hands-on experience in training, fine-tuning, optimizing, and deploying large language models
- Cloud Experience: Proficiency with public cloud infrastructure and services (e.g., AWS, Google Cloud, Azure) and familiarity with containerization technologies (e.g., Docker, Kubernetes)
- Problem-Solving Skills: Excellent problem-solving skills and the ability to thrive in a fast-paced, collaborative environment
- Communication Skills: Strong communication skills with the ability to simplify complex technical concepts for non-technical stakeholders
- Practical Experience: 3+ years of practical experience as a machine learning engineer, with demonstrated experience in providing technical guidance and support during customer interactions
What the job involves
- As a Machine Learning Engineer at Contextual AI, you will play a critical role in driving business value and solving real-world problems for our customers
- You will be responsible for designing, implementing, and deploying machine learning models to address practical challenges faced by our customers
- You will work closely with customers to onboard, enable use-cases, design templates and pipelines, and help drive the adoption of Contextual AI’s technology
- Technical Leadership: Own the technical aspects of customer conversation, design and lead technology evaluations, and integrated state-of-the-art research with our platform
- Machine Learning Development: Research, prototype, and implement state-of-the-art machine learning models and algorithms to address specific use cases and optimize performance metrics
- Platform Integration: Integrate machine learning solutions into production systems and ensure smooth deployment and maintenance
- Customer Engagement: Act as a trusted technical advisor and subject matter expert for our customers, building relationships with technical stakeholders, and guiding them through the adoption of Contextual AI’s technology
- Data Pipeline Development: Develop robust, scalable, and efficient pipelines for data preprocessing, feature engineering, model training, evaluation, and deployment
- Continuous Improvement: Collect instrumentation data and analytics to understand platform usage, drive insights, and suggest potential improvements
- Mentorship: Provide technical guidance and mentorship to junior team members, fostering a culture of continuous learning and knowledge sharing
Our take
Founded by former Facebook research scientists, Contextual AI is building customisable, scalable and trustworthy Large Language Models for use by enterprises. Its main product is a tool to improve model performance so that users can build production-grade AI systems.
The backbone of this product is a technology that feeds curated information into AI models so that the LLM can have more context and up-to-date information. This helps to minimise AI “hallucinations”, an increasingly common problem for models like ChatGPT.
Contextual AI is currently working with companies in the finance, technology and media sectors. Since its impressive 2024 funding, it will no doubt seek growth, perhaps into other sectors. Either way, as AI models become more and more common in enterprise use, the future looks bright for Contextual AI.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (2 rounds)
Aug 2024
$80m
SERIES A
Jun 2023
$20m
SEED
Total funding: $100m
Company benefits
- Nnovative Environment: Be part of a forward-thinking company that values creativity and innovation
- Career Growth: Opportunities for professional development and career advancement
- Collaborative Culture: Work with a talented and supportive team dedicated to excellence
Company HQ
SoMa, San Francisco, CA
Leadership
Douwe Kiela
(CEO)Previously Adjunct Professor at Stanford University, Head of Research at Hugging Face and Research Scientist at Facebook. Was also the CEO and Founder of Brainstorm IT.
Amanpreet Singh
(CTO)Previously Research Team Lead at Hugging Face, Research Engineer at Facebook AI, and Mobile Maintainer at jQuery Foundation. Was also a Software Engineering Intern at Amazon.
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