Research Scientist - Voice AI Foundations
Deepgram$150,000 - $220,000/year
Full Time
Mid-level (3 to 4 years), Senior (5 to 8 years)
Not SpecifiedCompensation
Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Oil & Gas, Chemicals, Pharmaceuticals, Manufacturing, EnergyIndustries
Requirements
- 3+ years of experience in AI/ML engineering, with hands-on delivery of models
- Proficiency in working with foundation models (LLMs), including prompt engineering, evaluation, and (when relevant) fine-tuning
- Proficiency in RAG pipelines and integration with knowledge bases or vector databases
- Strong Python skills with experience using frameworks such as LangChain, Transformers, or similar
- Understanding of cloud-native development, model training workflows, and ML pipeline orchestration (e.g., data labeling, feature selection, model retraining)
- Proven ability to write clean, maintainable, and scalable code, following engineering best practices for testing, version control, and review
- A maker mindset with bias toward rapid iteration
Responsibilities
- Design and apply foundation models to domain-specific tasks, focusing on prompt engineering, reasoning workflows, and tool use with attention to accuracy, robustness, and real-world applicability
- Develop modular, production-ready agent workflows integrated with CDF and ATLAS AI, leveraging tools, memory, reasoning chains, and APIs
- Evaluate and integrate new GenAI tools, open-source frameworks, and APIs into ATLAS AI workflows
- Benchmark performance, tune retrieval and reasoning pipelines, and ensure scalability in real-world industrial deployments
- Work with solution engineers and customer teams to align models and agent behaviors with business value and industrial constraints
Skills
Key technologies and capabilities for this role
Questions & Answers
Common questions about this position
What are the key responsibilities of the AI/ML Engineer role?
Key responsibilities include model development with foundation models for domain-specific tasks using prompt engineering, designing modular agent architectures integrated with CDF and ATLAS AI, tech exploration with new GenAI tools, and system optimization through benchmarking and tuning pipelines.
What skills are required for this AI/ML Engineer position?
The role requires strong AI/ML engineering skills, expertise in designing and optimizing advanced AI models and agent architectures, prompt engineering, reasoning workflows, tool use, and the ability to integrate GenAI tools with industrial data platforms like CDF and ATLAS AI.
What is the salary or compensation for this role?
This information is not specified in the job description.
What are Cognite's company values?
Cognite's values are Impact (result-oriented), Ownership (embracing inclusivity and shared responsibilities), and Relentless (determined pursuit of innovation, viewing setbacks as growth opportunities).
Is this AI/ML Engineer role remote or office-based?
This information is not specified in the job description.
Cognite
Industrial data management for asset-heavy industries
About Cognite
Cognite specializes in managing industrial data and facilitating digital transformation for asset-heavy industries like oil and gas, power and utilities, and manufacturing. Its main product, Cognite Data Fusion, integrates and organizes data from various sources, making it easier for businesses to analyze and utilize this information effectively. This process, known as data contextualization, enhances the relevance of data for better decision-making. Cognite operates on a software-as-a-service (SaaS) model, allowing clients to subscribe to its software, which provides a consistent revenue stream and access to ongoing updates. Additionally, Cognite offers consulting services to assist clients in optimizing their use of the software. The company's goal is to help industries improve their operations through better data management and digital solutions.
Bærum, NorwayHeadquarters
2016Year Founded
$219.2MTotal Funding
SERIES_BCompany Stage
Data & Analytics, Industrial & Manufacturing, Enterprise SoftwareIndustries
501-1,000Employees
Benefits
Competitive Compensation + 401(k) with employer matching
Health, Dental, Vision & Disability Coverages with premiums fully covered for employees and all dependents
Unlimited PTO + flexibility to enjoy it
Paid Parental Leave Program
Learning & Development Stipends
Global Mobility & Exchange Program
Company Paid Friday Lunch via DoorDash + Fully Stocked Fridges in the offices
Risks
Emerging industrial AI startups pose a threat to Cognite's market share.
Geopolitical tensions could disrupt operations in key regions like the Middle East.
Reliance on cloud providers introduces risks related to data security and outages.
Differentiation
Cognite Data Fusion integrates and contextualizes data for asset-heavy industries.
Cognite offers a subscription-based SaaS model, ensuring continuous software updates.
Cognite's solutions enhance safety, sustainability, and efficiency in industrial operations.
Upsides
Cognite's partnership with Google Cloud enhances scalability and security for data management.
The launch of Cognite Embedded opens new innovation avenues for industrial software builders.
Cognite's joint venture with Saudi Aramco expands its influence in the MENA region.
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