Research Scientist

StrainX Biotech; Hyderabad; On-site; INR 3,500,000 - 6,000,000; Full time

Benefits offered by this job

Professional development through in‑h

Educational assistance for continuing

Medical, Life and Personal Accident保险

Life insurance for families

Personal loan assistance

Employee Stock Investment Plan (ESIP)

12 weeks Paternity leave

Onsite fitness center, recreation, and

Transport facility

Child day care facility for women

Cricket grounds and gymnasium

Library

Health Center with doctor availability

HDFC ATM on campus

Job summary

Franklin Templeton in Hyderabad seeks a mid-senior AI researcher to translate frontier research into production-ready capabilities. You will collaborate with product, engineering, data, and business teams to design agentic systems, evaluation methods, and robust safety practices.

The role emphasizes experiments, open collaboration, mentoring, and producing reusable research outputs, with a focus on measurable business value in financial services.

Qualifications

• PhD or equivalent in AI/ML/CS or related field.
• At least 1 year of industry AI/ML research experience.
• Evidence of impact through publications, patents, open-source work, or deployed systems.
• Experience translating research into reusable platforms, services, benchmarks, or practices.
• Research leadership, mentoring, teaching, or community-building experience preferred.

Responsibilities

• Research agent planning, tool use, memory, multi-step workflows, and multi-agent coordination.
• Design capability evaluations, safety testing, reliability testing, and alignment approaches.
• Analyse agent behavior, identify failure modes, and establish monitoring.
• Develop systems learning from feedback, experiments, interactions, evaluations, and outcomes.
• Build prototypes and production-adjacent artifacts beyond papers and demos.
• Create reusable agent skills, evaluation harnesses, datasets, benchmarks, and models.
• Develop reference architectures, libraries, and clear technical documentation.

Skills

Deep machine learning

Experimental design

Statistical reasoning

Reproducibility expertise

CI/CD tooling (Git, Docker)

Cloud computing environments

Agentic systems development

Evaluation harnesses

Alignment, robustness, privacy, safety

Reinforcement learning in finance

Education

PhD or equivalent in AI/ML/CS or related field

1+ year industry AI/ML research experience

Tools

Git

Docker

Cloud platforms

Job description

About The Department

Our AI research function transforms frontier research into trusted capabilities that create measurable business value. Researchers collaborate with product, engineering, data, and business teams to develop agentic systems, evaluation methods, alignment approaches, and recursive-learning solutions. The team values rigorous experimentation, practical impact, open collaboration, and reusable research. Joining offers opportunities to influence production systems, publish meaningful work, mentor others, and strengthen enterprise AI capabilities.

How you will add value?

• You will research agent planning, tool use, memory, multi-step workflows, and multi-agent coordination.
• You will research human-in-the-loop operations for agentic artificial intelligence systems.
• You will design capability evaluations, safety testing, reliability testing, and alignment approaches.
• You will analyse agent behaviour, discover failure modes, and establish continuous monitoring.
• You will develop systems learning from feedback, experiments, interactions, evaluations, and operational outcomes.
• You will build prototypes and production-adjacent artifacts beyond papers, notebooks, and demonstrations.
• You will create reusable agent skills, evaluation harnesses, datasets, benchmarks, and models.
• You will develop reference architectures, libraries, and clear technical documentation.

Strategic Responsibilities

• You will understand workflows, customer needs, operational constraints, and adoption barriers.
• You will select research questions with credible paths to measurable impact.
• You will monitor external research and reproduce important results where useful.
• You will assess what is durable, useful, and appropriate for the organization.
• You will prioritize research that creates reusable internal capabilities.

Team & Collaboration

• You will identify valuable research problems with product, engineering, data, and business teams.
• You will contribute findings to internal communities of practice and shared technical platforms.
• You will help others understand, reuse, test, and improve your research.
• You will publish and present research that advances the field.
• You will strengthen the organization’s technical reputation through credible research.

Work Shift Timings – 2:00 PM – 11:00 PM IST

At Franklin Templeton, we believe your benefits should support your life, your goals, and your future. That’s why we offer a comprehensive Total Rewards package designed to help you thrive both personally and professionally.

Highlights Of Our Benefits Include

• Professional development growth opportunities through in-house classes and over 150 Web-based training courses
• An educational assistance program to financially help employees seeking continuing education
• Medical, Life and Personal Accident Insurance benefit for employees. Medical insurance also cover employee’s dependents (spouses, children and dependent parents)
• Life insurance for protection of employees’ families
• Personal accident insurance for protection of employees and their families
• Personal loan assistance
• Employee Stock Investment Plan (ESIP)
• 12 weeks Paternity leave
• Onsite fitness center, recreation center, and cafeteria
• Transport facility
• Child day care facility for women employees
• Cricket grounds and gymnasium
• Library
• Health Center with doctor availability
• HDFC ATM on the campus

Franklin Templeton is an Equal Opportunity Employer. We are committed to providing equal employment opportunities to all applicants and existing employees, and we evaluate qualified applicants without regard to ancestry, age, color, disability, genetic information, gender, gender identity, or gender expression, marital status, medical condition, military or veteran status, national origin, race, religion, sex, sexual orientation, and any other basis protected by federal, state, or local law, ordinance, or regulation.

Artificial intelligence or automated tools may be used to assist in the screening, assessment, or selection of applicants for this position.

What will help you be successful in this role?Experience, Education & Certifications

• PhD or equivalent in artificial intelligence, machine learning, computer science, statistics, operations research, robotics, computational linguistics, or a closely related field from a strong research institution; or a PhD in another field paired with a demonstrable, substantial pivot into AI.
• Minimum one year of relevant industry experience in Artificial Intelligence or Machine Learning research.
• Evidence of impact through publications, patents, open-source work, or deployed systems.
• Experience translating research into reusable platforms, services, benchmarks, or practices.
• Research leadership, mentoring, teaching, or technical community-building experience is preferred.

Technical Skills

• Deep machine learning, experimental design, statistical reasoning, and reproducibility expertise.
• Experience with modern enterprise CI/CD tooling (Git, Docker, etc.) and cloud computing environments.
• Experience developing agentic systems using frameworks or custom orchestration.
• Expertise in evaluation harnesses, regression testing, simulations, and human evaluation.
• Knowledge of alignment, robustness, privacy, security, and human oversight.
• Reinforcement learning or regulated financial-services experience is advantageous.

Soft Skills

• Prioritize measurable real-world impact alongside intellectual novelty.
• Produce documented, testable, reusable, discoverable, and maintainable research outputs.
• Share knowledge through code, writing, teaching, mentorship, workshops, hackathons, and collaboration.
• Use evidence rigorously while testing quickly and discarding weak hypotheses.
• Approach users, workflows, constraints, incentives, and business domains with humility and curiosity.
• Consider usefulness, trust, adoption, fairness, and durability alongside technical performance.
• Give credit, enable contributions, and balance publication goals with open-source and platform thinking.

Seniority levelMid-Senior level

Employment typeFull-time

IndustriesFinancial Services