Senior Machine Learning Engineer – LLM & Generative AI
Embark on a transformative journey with Cognite, a global SaaS forerunner in leveraging data to unravel complex business challenges through our cutting-edge Cognite Data Fusion (CDF) platform. We were awarded the 2022 Technology Innovation Leader for Global Digital Industrial Platforms . In the realm of industrial digitalization, we stand at the forefront, reshaping the future of Oil & Gas, Manufacturing and Energy sectors. As an integral part of the esteemed Aker family, Cognite brings forth a legacy of innovation and excellence. Excitingly, we are set to extend our footprint to the vibrant landscapes of India, which opens the door for you to be part of the expansion from the beginning. Join us in this venture where data meets ingenuity, and together, we forge the path to a smarter, more connected industrial future.
The rapid advances of Artificial intelligence (AI), especially around Generative AI, and in particular LLMs like OpenAI GPT family of models, have driven innovations starting to disrupt existing market spaces across industry. Many businesses are betting on AI as the next growth opportunity.
Who You Are:
We are looking for a highly motivated and talented Senior Machine Learning Engineer to join our AI team. The ideal candidate will have experience in Large Language Modeling (LLM) and DataOps. We are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, then this is the perfect job for you!
Opportunity: Machine learning experts on our team can utilize applied science and software development skills to help tweak Foundation Models that help us address some of the hardest problems towards our vision in making insights from complex Industrial data simple & easy to access. You will work in an exciting and fast-paced environment, collaborating closely with multiple teams across the company. You will work as part of an organization that brings together talent from diverse backgrounds including software engineering, big data, machine learning, AI, and Industrial data architects making our team an exciting place to work. We value and encourage diversity in the belief that our differences make us and our products better.
This position offers a unique chance to work on state-of-the-art language models and contribute to transformative research with the vision of saving lives with Industrial Data. You will be part of a dynamic team of researchers and engineers who are passionate about pushing the boundaries of machine learning and natural language understanding in the Industrial domain. Join us and make a significant impact on the future of Industrial DataOps.
What You’ll Do:
- Collaborate with researchers and engineers to design, develop, and refine large language models and generative models for various applications.
- Utilize your expertise in machine learning and natural language processing to develop novel algorithms and methodologies for generative modeling tasks.
- Implement, train, and fine-tune LLM and GPT-like models on large-scale datasets to ensure optimal performance and accuracy.
- Stay up to date with the latest research advancements and techniques in the field of language modeling, generative modeling, and machine learning.
- Deliver the next generation of innovation in trustworthy Industrial Data Insights & Collaboration
Who You Are:
- Extensive software engineering experience in building high performance, large-scale ML systems (Preferably 3 to 5 years of industry experience in the relevant fields).
- Strong communication skills and the ability to work effectively in a collaborative research environment.
- Demonstrated leadership abilities, with experience in guiding and mentoring a team of ML engineers.
- Excellent problem-solving and troubleshooting abilities, along with a strong analytical mindset and persistence in resolving problems.
- Strong theoretical and practical background in NLP including experience with state-of-the-art LLM architectures optimized for handling large context and low inference cost.
- Advanced degree, ideally a Ph.D., in Computer Science, Electrical Engineering, or a related field with specialized research in areas such as machine learning, NLP, Large Language Models (LLMs), multi-modal foundation models, and generative AI techniques.
- Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow, etc.) and libraries commonly used in NLP and Generative AI.
- Solid programming skills in Python and the ability to write clean, efficient, and well-documented code.
- 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects.
- Experience with distributed parallel training, large-scale multi-modal foundation and generative models strongly preferred.
- Collaborate on modeling techniques to support the full spectrum of LLM tuning including prompt engineering, instruction tuning, Reinforcement Learning from Human Feedback (RLHF), parameter-efficient tuning, and fine-tuning strongly preferred.
- Familiarity with training multi-modal foundation models and relevant frameworks strongly preferred.
- Familiarity with cloud-based infrastructure and experience deploying large-scale machine learning models in production environments.
- Experience with RAG, dual encoders, or related fields strongly preferred.
- Experience with JAX.
- A track record of publications and contributions to the machine learning and natural language processing communities strongly preferred.
Why choose Cognite?
- Join us in making a real and lasting impact in one of the most exciting and fastest-growing new software companies in the world.
- We have repeatedly demonstrated that digital transformation, when anchored on strong DataOps, drives business value and sustainability for clients and allows front-line workers, as well as domain experts, to make better decisions every single day.
- Cognite Earns 2023 Microsoft Partner of the Year Award; Recognized as a Global Leader in Energy & Resources and Industrials & Manufacturing
- And just recently, Frost & Sullivan named Cognite a Technology Innovation Leader !
- Built In 2024 Best Places to Work in Austin, TX and Houston, TX
A snapshot of our many perks and benefits as a Cogniter
- Competitive Compensation including base plus bonus
- 401(k) with 4% employer matching
- Health, Dental, Vision & Disability Coverages with premiums fully covered for employees and all dependents
- Unlimited PTO + flexibility to enjoy it
- 18 Company Holidays including the week between Christmas & New Years
- Paid Parental Leave Program
- Employee Stock Purchase Program (ESPP)
- Employee Referral Program
- Company Paid Friday Lunch via DoorDash + Fully Stocked Fridges in the offices
- Join a team of 70 different nationalities 🌐 with Diversity, Equality and Inclusion (DEI) in focus 🤝.
- A highly modern and fun working environment with sublime culture across the organization, follow us on Instagram @ cognitedata 📷 to know more
- Opportunity to work with and learn from some of the best people on some of the most ambitious projects found anywhere, across industries
- Join our HUB 🗣️ to be part of the conversation directly with Cogniters and our partners.
- Paid mobile phone and WiFI
- A pet lover? Get the chance to meet Spot 🐶!
Cognite is a global industrial SaaS company that was established with one clear vision: to rapidly empower industrial companies with contextualized, trustworthy, and accessible data to help drive the full-scale digital transformation of asset-heavy industries around the world. Our core Industrial DataOps platform, Cognite Data Fusion™, enables industrial data and domain users to collaborate quickly and safely to develop, operationalize, and scale industrial AI solutions and applications to deliver both profitability and sustainability. Visit us at www.cognite.com and follow us on Twitter @CogniteData or LinkedIn: https://www.linkedin.com/company/cognitedata
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