Senior Data Scientist — Core AI R&D
Location: Remote
Employment Type: Full-time
Preferred: Time-zone overlap with India working hours
About the Opportunity
Our client is a fast-growing technology company developing advanced AI-powered solutions for industrial analytics and operational intelligence. As they continue to expand their Core AI Research & Development team, we are seeking a Senior Data Scientist with strong research and applied experience in one or more of the following areas:
- Time-series modeling for industrial sensor data
- Reinforcement learning and prescriptive decision-making
- Knowledge representation, graph learning, and multi-modal AI systems
This role offers the opportunity to work on cutting-edge AI research while driving real-world business impact through production-grade solutions.
Key Responsibilities
Time-Series Modeling
- Develop and enhance modern deep learning models for time-series analysis using large-scale industrial sensor datasets.
- Design retraining and adaptation pipelines to maintain model performance as data evolves over time.
- Apply transfer learning and low-label adaptation techniques to support new equipment types and sensor sources.
- Improve prediction accuracy across multiple asset categories.
Reinforcement Learning & Prescriptive Intelligence
- Design reinforcement learning frameworks that generate actionable operational recommendations.
- Develop optimization approaches that balance multiple business and operational constraints.
- Implement preference-learning techniques leveraging expert feedback and validated operational outcomes.
- Collaborate with product and engineering teams to integrate prescriptive recommendations into production environments.
Knowledge Representation & Multi-modal AI
- Expand and enhance domain knowledge graphs representing industrial assets, failure modes, and recommended actions.
- Apply graph-based learning methods to improve reasoning and knowledge transfer across equipment types.
- Integrate structured and unstructured data sources, including technical documentation, engineering diagrams, operator notes, and conversational data.
- Identify patterns and insights that improve model generalization across industries and customer segments.
Research & Collaboration
- Translate state-of-the-art research into scalable, production-ready solutions.
- Mentor junior data scientists and contribute to the growth of the research organization.
- Collaborate with cross-functional teams to bring AI innovations into customer-facing products.
- Define, monitor, and improve quality metrics for predictive and prescriptive AI systems.
- Contribute to patents, publications, and open-source initiatives where appropriate.
Required Qualifications
Education
- PhD preferred, or Master’s degree in Computer Science, Statistics, Applied Mathematics, Electrical Engineering, or a related field.
- Exceptional candidates with equivalent industry experience will also be considered.
Technical Experience
- 5+ years of hands-on machine learning experience with deep expertise in at least one of:
- Time-series modeling
- Reinforcement learning
- Graph machine learning and knowledge representation
- Strong Python programming skills.
- Experience with modern deep learning frameworks (PyTorch preferred).
- Practical knowledge of reinforcement learning methodologies and production-grade RL frameworks.
- Experience working with knowledge graphs, graph neural networks, embeddings, or related technologies.
- Familiarity with retrieval-augmented systems, vector databases, and unstructured data processing.
- Experience with cloud platforms and managed machine learning services.
- Strong software engineering practices, including version control, testing, and reproducible experimentation.
Soft Skills
- Strong product mindset with the ability to move research into production.
- Excellent communication skills and ability to work with both technical and non-technical stakeholders.
- Comfortable working in fast-paced environments with evolving priorities.
- Experience collaborating across distributed and international teams.
Nice to Have
- Experience in predictive maintenance, condition monitoring, industrial AI, or vibration analysis.
- Knowledge of physics-informed machine learning or causal inference techniques.
- Publications in leading ML conferences or journals.
- Experience with agentic AI systems, LLM evaluation, or advanced generative AI applications.
What Our Client Offers
- Opportunity to work on challenging AI research problems with direct business impact.
- Collaborative environment combining research excellence with product delivery.
- Remote-first culture with a globally distributed team.
- Exposure to large-scale industrial datasets and real-world AI applications.
- Competitive compensation package and long-term growth opportunities.
Looking forward to your reply!