Senior Data Scientist — Core AI R&D

Hiretop; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Hiretop seeks a Senior Data Scientist to lead research and develop production-ready AI solutions for industrial analytics and operational intelligence. You will influence time-series modeling, graph learning, and prescriptive ML methods while collaborating with product and engineering teams.

The role emphasizes translating cutting-edge research into scalable systems with cross-functional partners and opportunities for patents, publications, and open-source contributions.

Qualifications

• PhD preferred, or Master’s in Computer Science, Statistics, Applied Mathematics, Electrical Engineering, or related field.
• 5+ years hands-on ML experience with time-series modeling, RL, or graph ML.
• Experience with PyTorch and modern ML frameworks.
• Knowledge graphs, graph neural networks, embeddings, or related tech.
• Retrieval-augmented systems, vector databases, unstructured data processing.
• Cloud platforms and managed ML services.
• Software engineering practices: version control, testing, reproducible experiments.
• Excellent communication and ability to move research to production.

Responsibilities

• Develop and enhance deep learning models for time-series analysis on industrial sensor data.
• Design retraining and adaptation pipelines to maintain performance as data evolves.
• Apply transfer learning and low-label adaptation for new equipment and sensors.
• Improve prediction accuracy across asset categories and timescales.
• Design RL frameworks for actionable operational recommendations.
• Develop optimization approaches balancing business and operational constraints.
• Integrate prescriptive recommendations into production environments.
• Expand domain knowledge graphs for assets, failures, and actions.
• Apply graph-based learning to improve cross-asset reasoning.
• Combine structured and unstructured data sources for robust models.
• Identify patterns that generalize across industries and customers.

Skills

Time-series modeling

Reinforcement learning

Graph machine learning

Knowledge representation

Retrieval-augmented systems

Vector databases

Unstructured data processing

Cloud platforms

Software engineering practices

Education

PhD preferred or Master’s degree in CS/Stats/Applied Math/EE

Tools

PyTorch

Job description

Location:Remote
Employment Type:Full-time
Preferred:Time-zone overlap with India working hours

About the Opportunity

Our client isafast-growing technology company developing advanced AI-powered solutions for industrial analytics and operational intelligence. Asthey continue toexpand their Core AIResearch &Development team, weare seeking aSenior Data Scientistwith strong research and applied experience inone ormore ofthe following areas:

• Reinforcement learning and prescriptive decision-making
• Knowledge representation, graph learning, and multi-modal AIsystems

This role offers the opportunity towork oncutting-edge AIresearch 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 tomaintain model performance asdata evolves over time.
• Apply transfer learning and low-label adaptation techniques tosupport new equipment types and sensor sources.
• Improve prediction accuracy across multiple asset categories.
• 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 tointegrate prescriptive recommendations into production environments.
• 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 tothe growth ofthe research organization.
• Collaborate with cross-functional teams tobringAI innovations into customer-facing products.
• Define, monitor, and improve quality metrics for predictive and prescriptive AIsystems.
• Contribute topatents, publications, and open-source initiatives where appropriate.

Required Qualifications

Education

• PhDpreferred, orMaster’s degree inComputer Science, Statistics, Applied Mathematics, Electrical Engineering, orarelated field.
• Exceptional candidates with equivalent industry experience will also beconsidered.

Technical Experience

• 5+years ofhands-on machine learning experience with deep expertise inatleast oneof:
  • Time-series modeling
  • Reinforcement learning
  • Graph machine learning and knowledge representation
• Experience with modern deep learning frameworks (PyTorch preferred).
• Practical knowledge ofreinforcement learning methodologies and production-grade RLframeworks.
• Experience working with knowledge graphs, graph neural networks, embeddings, orrelated 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 tomove research into production.
• Excellent communication skills and ability towork with both technical and non-technical stakeholders.
• Comfortable working infast-paced environments with evolving priorities.
• Experience collaborating across distributed and international teams.

Nice toHave

• Experience inpredictive maintenance, condition monitoring, industrialAI, orvibration analysis.
• Knowledge ofphysics-informed machine learning orcausal inference techniques.
• Publications inleadingML conferences orjournals.
• Experience with agentic AIsystems, LLMevaluation, oradvanced generative AIapplications.

What Our Client Offers

• Opportunity towork onchallengingAI research problems with direct business impact.
• Collaborative environment combining research excellence with product delivery.
• Remote-first culture with aglobally distributed team.
• Exposure tolarge-scale industrial datasets and real-world AIapplications.
• Competitive compensation package and long-term growth opportunities.