Smartsheet is seeking a Senior Data Scientist to drive growth and customer retention through Applied AI and advanced analytics. With thousands of subscribing organizations and millions of users, you will have the opportunity to make a meaningful impact by leveraging data science to drive Sales, Customer Success, and Monetization strategies. You are curious, have strong data science and machine learning skills and the ability to communicate key insights effectively. You will work primarily with Go to Market Teams and will be a part of Smartsheet's Data Science & Business Intelligence team.

You Will:

• Partner with Sales and Customer Success teams, understand their goals, and execute on opportunities to draw relevant insights and drive tangible impact
• Develop and implement machine learning based Cross-sell/Upsell models and Product Recommender models to drive Sales & Monetization
• Build and deploy predictive models for Customer Churn and identify proactive churn risk prediction signals to drive retention
• Drive the full analytics lifecycle from understanding the business objective, analyzing the data to developing automated reporting and visualizations
• Collaborate with cross-functional teams to integrate data science solutions into business processes
• Effectively present analysis to both technical and non-technical audiences and give data-based recommendations to encourage data-driven decisions 
• Drive a data culture within the Go To Market  teams

You Have:

• Bachelor's degree and 8+ years of experience (or 10+ years of experience)
• Extensive knowledge and practical experience in several of the following areas: Applied AI, machine learning, statistics, propensity modeling, churn prediction and recommender systems
• Proficient analytical skills for problem solving; can perform descriptive analysis, diagnostic analysis, predictive analysis and prescriptive analysis.
• Strong programming skills in Python or R
• Proficient in SQL and skilled in visualization tools (ex. Tableau)
• Strong track record of forming effective cross-functional partnerships
• Experience using data to meaningfully impact Sales & Customer Success strategy execution
• Experience communicating analysis clearly to others
• Ability to research and learn new technologies, tools, and methodologies
• Ability to thrive in a dynamic environment, find opportunities and execute in both independent and collaborative environments
• As a senior member of the data science team help mentor and help grow members of the team

The Role

Lead the maturation of Securly's content classification system — building the ML infrastructure that determines, at scale, whether web content is appropriate for K-12 students, and establishing the rigorous evaluation framework that product and leadership teams depend on.

This is applied ML with direct student safety impact — not research. You will lead a significant uplift of Securly's classification models: refactoring binary models to proper multiclass classification, building labeled evaluation datasets, and producing standardized model cards with per-category precision, recall, F1, and confusion matrix analysis.

At L5, you are the technical leader of the data science function for content safety. You will define the evaluation methodology the team follows, set the standard for what a model card must contain before a model ships, mentor the team on applied ML rigor, and serve as the interface between data science and engineering on production integration constraints.

What It Means to Be L5 at Securly

L5 at Securly is a Staff Engineer. You are the technical owner, not just an implementer.

• Drive technical direction for your initiative end-to-end: from architecture to production, with minimal oversight from your engineering manager.
• Identify and resolve ambiguity in requirements, system boundaries, and design tradeoffs without waiting for a fully-formed spec.
• Mentor L3/L4 engineers on the team: code reviews, design feedback, pairing, and raising the bar for what production-quality work looks like.
• Partner with your L6 technical lead and the Distinguished Engineer on architectural decisions, surfacing tradeoffs clearly rather than deferring them upward.
• Contribute to cross-team engineering standards: you are expected to influence practices beyond your immediate squad.
• Translate technical context into clear written artifacts that non-engineers (PM, Support, Leadership) can act on.
• Participate in on-call rotation and own the full incident lifecycle for your system: detection, diagnosis, resolution, and retrospective.

What You'll Do

• Define the evaluation methodology for content classification at Securly: establish what a model card must contain and hold every model release to that standard before it ships.
• Lead the multiclass refactor of Securly's content classification models: redesign binary models to handle multi-label, multi-class content categories (Adult Content, Violence, Self-Harm, Social Media, and others).
• Build and maintain labeled evaluation datasets with robust annotation workflows; address class imbalance and label noise systematically; document dataset curation decisions in a versioned data card.
• Connect offline evaluation to production monitoring — surface classification drift and error patterns before they become customer-facing issues.
• Investigate and resolve misclassification errors: false positives (over-blocking) and false negatives (under-blocking); produce written root cause analyses.
• Build and maintain training data pipelines: ingestion, cleaning, labeling, and versioning at scale.
• Mentor the existing AI team on evaluation methodology, model development practices, and data science communication rigor.
• Communicate precision/recall tradeoffs to product managers and engineers; produce executive-level summaries of classification quality for leadership.
• Collaborate with engineering to integrate model outputs into the production filtering stack with appropriate latency and reliability constraints.
• Research and prototype improvements: feature representations, model architectures, active learning for label efficiency, domain adaptation for emerging content categories.

Skills & Requirements

Who You Are

• You have shipped ML models to production and lived with the consequences — you know what model drift looks like and how to catch it before it becomes a customer issue.
• You treat evaluation as a first-class engineering artifact. A model without a model card is not finished — and you set and enforce that standard for the team.
• You define the methodology, not just apply it. You produce the evaluation framework that other data scientists use, and you hold them to it.
• You can communicate precision/recall tradeoffs to a product manager and to a senior engineer in the same conversation, calibrated to each audience.
• You are energized by problems with real stakes: a false negative in Self-Harm classification is not an acceptable error rate.
• You mentor by example and by expectation: your code, your analysis, and your documentation set the standard.

About Securly

Benefits

The Role

The Senior Data Scientist will lead the maturation of Securly's content classification system — building the ML infrastructure that determines, at scale, whether web content is appropriate for K-12 students, and establishing the rigorous evaluation framework that product and leadership teams depend on.

This is applied ML with direct student safety impact — not research. You will lead a significant uplift of Securly's classification models: refactoring binary models to proper multiclass classification, building labeled evaluation datasets, and producing standardized model cards with per-category precision, recall, F1, and confusion matrix analysis.

At L5, you are the technical leader of the data science function for content safety. You will define the evaluation methodology the team follows, set the standard for what a model card must contain before a model ships, mentor the team on applied ML rigor, and serve as the interface between data science and engineering on production integration constraints.

What It Means to Be L5 at Securly

L5 at Securly is a Staff Engineer. You are the technical owner, not just an implementer.

• Drive technical direction for your initiative end-to-end: from architecture to production, with minimal oversight from your engineering manager.
• Identify and resolve ambiguity in requirements, system boundaries, and design tradeoffs without waiting for a fully-formed spec.
• Mentor L3/L4 engineers on the team: code reviews, design feedback, pairing, and raising the bar for what production-quality work looks like.
• Partner with your L6 technical lead and the Distinguished Engineer on architectural decisions, surfacing tradeoffs clearly rather than deferring them upward.
• Contribute to cross-team engineering standards: you are expected to influence practices beyond your immediate squad.
• Translate technical context into clear written artifacts that non-engineers (PM, Support, Leadership) can act on.
• Participate in on-call rotation and own the full incident lifecycle for your system: detection, diagnosis, resolution, and retrospective.

What You'll Do

• Define the evaluation methodology for content classification at Securly: establish what a model card must contain and hold every model release to that standard before it ships.
• Lead the multiclass refactor of Securly's content classification models: redesign binary models to handle multi-label, multi-class content categories (Adult Content, Violence, Self-Harm, Social Media, and others).
• Build and maintain labeled evaluation datasets with robust annotation workflows; address class imbalance and label noise systematically; document dataset curation decisions in a versioned data card.
• Connect offline evaluation to production monitoring — surface classification drift and error patterns before they become customer-facing issues.
• Investigate and resolve misclassification errors: false positives (over-blocking) and false negatives (under-blocking); produce written root cause analyses.
• Build and maintain training data pipelines: ingestion, cleaning, labeling, and versioning at scale.
• Mentor the existing AI team on evaluation methodology, model development practices, and data science communication rigor.
• Communicate precision/recall tradeoffs to product managers and engineers; produce executive-level summaries of classification quality for leadership.
• Collaborate with engineering to integrate model outputs into the production filtering stack with appropriate latency and reliability constraints.
• Research and prototype improvements: feature representations, model architectures, active learning for label efficiency, domain adaptation for emerging content categories.

Skills & Requirements

Who You Are

• You have shipped ML models to production and lived with the consequences — you know what model drift looks like and how to catch it before it becomes a customer issue.
• You treat evaluation as a first-class engineering artifact. A model without a model card is not finished — and you set and enforce that standard for the team.
• You define the methodology, not just apply it. You produce the evaluation framework that other data scientists use, and you hold them to it.
• You can communicate precision/recall tradeoffs to a product manager and to a senior engineer in the same conversation, calibrated to each audience.
• You are energized by problems with real stakes: a false negative in Self-Harm classification is not an acceptable error rate.
• You mentor by example and by expectation: your code, your analysis, and your documentation set the standard.

About Securly

Benefits

ABOUT THE TEAM

Anduril’s Tactical Recon & Strike (TRS) is a division with two missions: 1) build highly capable autonomous drones, and 2) build solid rocket motors at scale. We transform products like Ghost, Anvil, Bolt, and Altius from early concepts into fully operational capabilities by partnering closely with specialist engineering, operations, and production teams. Through our Anduril Rocket Motor Systems (RMS) team, we design and manufacture solid rocket motors using advanced materials, proprietary formulations, and high-volume production methods—delivering safe, reliable propulsion systems that support a wide range of mission requirements. TRS hires software engineers & hardware engineers, who are excited to build across a diverse and powerful portfolio—from autonomous aerial systems to high-performance solid rocket motors. Our teams contribute to highly capable autonomous robotics systems and propulsion products that operate reliably in the most demanding mission environment.

ABOUT THE JOB

As Senior Scientist, you will support the development of Anduril’s proprietary metal-powder fuel formulation through chemical and materials research and development. The right person for this role has hands-on skills in chemical and materials research and development and also in project management. If you are someone who is detail oriented and passionate about turning laboratory development into next-generation, real-world capabilities this role is for you.

WHAT YOU’LL DO

• Conduct experimental research under the guidance of a senior principal scientist.
• Collaborate with a multi-specialized team.
• Analyze data & plan experiments & make brief technical presentations.
• Support multi-threaded project management.

REQUIRED QUALIFICATIONS

• Master’s degree in chemical, materials science, or metallurgical engineering, chemistry, or related fields.
• Experience with air-sensitive chemistries, materials and techniques.
• Fundamental knowledge of material and chemical sciences.
• Experience in team-oriented project execution.
• Eligible to obtain and hold a U.S. Top Secret Security Clearance.

PREFERRED QUALIFICATIONS

• Ph. D degree in chemical, materials science, or metallurgical engineering, chemistry, or related fields.
• A preference for inorganic chemistry, metallurgical engineering, or material science.
• Experience with reactive metals
• Experience with surface chemistry.
• Experience with team project leadership & management. Well-developed soft skills for technical project collaboration.
• Experience with materials characterization techniques and interpretation (ICP, gravimetric analysis, microscopy, DSC, spectrometry, etc.).
• Experience with propellant or energetic materials.

About HG Insights

HG Insights is the pioneer of Revenue Growth Intelligence. For more than a decade, we have delivered comprehensive, AI-driven datasets on B2B buyers, technology adoption, IT spend, and buyer intent, sourced from billions of data points. Today, we are a trusted partner to Fortune 500 technology companies, hyperscalers, and innovative B2B vendors seeking precise go-to-market analytics and decision-making.

Through an evolving suite of AI agents that incorporate first-party data and buyer signals, HG Insights enables AI-powered GTM automation across sales, marketing, RevOps, and data analytics teams, modernizing GTM execution from strategy through activation.

Role Overview

The Applied Data Scientist - Research is a collaborative analytical partner to the Head of Data Science, contributing to the design and validation of GTM insights that power the Contextual Intelligence initiative.

You will co-develop insight logic, selecting signals, designing scoring frameworks, prototyping models in Python, and validating outputs. You will also contribute to the production-ready briefs that are implemented in the data production pipeline by the engineering team.

This role sits at the intersection of statistical modeling, structured data analysis, and applied AI. You are comfortable reasoning about how to measure something rigorously, how entities and relationships in a knowledge graph can be leveraged, and how to use LLMs as a practical tool in the insight development workflow, not as a subject of research, but as part of the toolkit.

What You Will Do

Insight & Model Development

• Co-develop scoring frameworks and metrics models, contributing to signal selection, weighting logic, and model structure across a range of GTM insight types (acquisition,expansion, retention, strategic)
• Prototype insight logic in Python notebooks: assembling features from HG's structured data assets, implementing model components, and stress-testing outputs.
• Design and run validation experiments to confirm that insight outputs are directionally correct, well-calibrated, and meaningful across the full vendor universe
• Contribute to ontology and entity design, thinking through how vendors, products, companies, and relationships should be structured to support a given insight, informed by a conceptual understanding of the knowledge graph schema

Production Brief Development

• Translate insight designs into clear, implementation-ready production briefs 
• Document model specifications precisely: component definitions, feature engineering, aggregation logic, edge case handling, and expected output distributions
• Participate in handoff reviews with the production function, answering implementation questions and refining specs based on feasibility feedback

Insight Research & Discovery

• Contribute to the prioritized insights catalog, researching new insight ideas, assessing data availability, and framing feasibility
• Stay current on GTM data science approaches, competitive intelligence methodologies, and relevant analytical techniques that could expand the insight library

What We're Looking For

Core Skills

• Statistical modeling depth: Ability to design and implement a range of scoring and metrics models from first principles; comfortable with component weighting, normalization, signed rate-of-change metrics, composite aggregation, and distribution analysis; knows when a technique is appropriate and why 
• Python for analytical prototyping: Strong notebook-based Python for data manipulation, feature construction, model prototyping, and output validation; pandas, NumPy, and Scikit are daily 
• SQL: Proficient in querying structured data at scale; used for signal extraction, feature derivation, and validation checks across large vendor and company datasets
• Analytical rigor & validation thinking: Ability to critically evaluate whether a model is measuring what it claims to measure; designs validation experiments, checks edge cases, and flags when outputs don't pass a sanity check
• Clear technical communication: Able to translate analytical logic into precise written specifications; the production brief is a key deliverable 

Applied AI & Graph Literacy

• LLM API usage: Hands-on experience using Claude, GPT, or equivalent APIs as a practical tool; can design effective prompts, integrate LLM steps into an analytical workflow, and evaluate output quality critically
• Knowledge graph concepts: Conceptual understanding of how entities, relationships, and properties are structured in a graph; able to reason about how graph-derived features (e.g., vendor-product-company traversals) should inform insight design, without necessarily writing production Cypher 

Nice to Have

• GTM/Management Consulting, or IT Research experience, familiarity with concepts like install base, intent signals, competitive intelligence, and market analysis. Experience writing Cypher or querying graph-structured data directly
• Experience working collaboratively with engineering, product and GTM teams
• Experience in a B2B SaaS or data products environment

Tools & Environment

Primary

• Python (pandas, NumPy, scipy, Jupyter)
• SQL
• LLM APIs (Claude, GPT)
• Git and version control

Working Knowledge

• Databricks
• Cloud storage 
• Knowledge graph concepts 

Simtra BioPharma Solutions (Simtra) is a world-class Contract Development Manufacturing Organization, partnering with pharmaceutical and biotech companies to bring their sterile injectable products to market. With facilities in Bloomington, Indiana, US and Halle/Westfalen, Germany, we offer a wide range of delivery systems including pre-filled syringes, liquid/lyophilized vials, diluents for reconstitution, powder-filled vials and sterile crystallization.  

Our product types include biologics and small molecules, cytotoxics, highly potent compounds, diluents for reconstitution and vaccines – which are all directly injected into patients worldwide.  As such, there is a strong emphasis on quality and continuous improvement at Simtra.  We hold ourselves to the highest quality and regulatory standards.

While our primary focus is cGMP manufacturing, we offer many support services including formulation and development, lyophilization optimization, global regulatory support and secondary packaging.  Our teams are driven to help clients scale, innovate and bring life-changing medicines to patients worldwide.

Why join Team Simtra? Because we:

Make it HAPPEN – We bring a growth mindset to every opportunity, developing new skillsets and exceeding our expectations and those of our customers.

Make it TOGETHER – We work as one, respecting each voice and tapping into our unique strengths across teams—so we can solve problems in new ways.

Make it RIGHT – We hold ourselves to a high standard of excellence, fulfilling our commitments to the customer, their patients, and our team members.

Make it COUNT – We take pride in our day-to-day work, knowing the impact we make – taking on challenges big and small to improve patient health.

The role:

The Development Scientist role is responsible for independently managing development projects and investigating improvements of technology that advance formulation development, process development, and manufacturing at Simtra. This role is also responsible for training scientists in formulation and process development for injectable products. The scientist reports directly to the Global Senior Scientist.

The responsibilities:

• Independently design and manage research studies that demonstrate the scientific capabilities at Simtra, solve challenging process development problems for potential clients, and that can be published in peer-reviewed journals and presented at scientific meetings.
• Collaborate with scientists in Bloomington and Halle to introduce potential new clients to Simtra, learn about their molecule / project, and propose possible directions for developing the product.
• Collaborate with the development scientists at both sites to overcome possible challenges in the development of a product.
• Investigate possible solutions to challenges that may be encountered during product development.
• Develop and utilize a digital twin during conjugation and purification of antibody drug conjugates and possibly other areas of development and manufacturing.
• Develop, implement, and optimize techniques and procedures in the field of formulation and lyophilization development or analytical development and validation. Develop a deeply differentiated technical skill set to contribute to department capabilities for product development.
• Sought out by other teams and individuals to offer technical advice; may act as coach, mentor, supervisor, and technical advisor to junior members within the discipline.
• Implement new or improved techniques and procedures around specific tasks. Apply state-of-the-art techniques in the area of expertise to develop new or improved products.
• Apply specialized technical and theoretical knowledge in creative ways to a broad range of difficult problems. Contribute to technical feasibility analysis, which incorporates multiple disciplines where new and unproven methods and technologies are required. Generate innovative solutions to highly complex problems where little clear precedence exists. Incorporate advanced theories, methods and technologies from around the world to develop new innovative products/processes.
• Examine the use of predictive modeling and data analysis for formulation and process development to improve platforms for client projects.
• Utilize operational excellence and statistical tools to improve experimental design, process efficiency, or quality/compliance.
• In addition to having an in-depth knowledge and understanding of GxP and related regulations and guidance, is able to provide expert insights into such regulations so as to facilitate efficient product registration and/or is an active participant in the generation, review, adoption and interpretation of such regulations.
• Maintain current knowledge of relevant quality and other regulatory requirements related to research and development (product development, design and safety) to ensure compliance in all research, data collection and reporting activities.
• Investigate routes of collaborating with start-ups or other companies to obtain funding for research and development initiatives.
• Interact and collaborate with Sales, Marketing, and Program Management groups to professionally introduce potential new clients to Simtra Development and Pre-Commercial Services as well as other teams and capabilities.
• Develop and conduct scientific training programs in formulation and process development for BDEs, PM, and clients in collaboration with business development.

Required Qualifications:

• Bachelor's degree in Chemistry, Biochemistry, Pharmaceutical Science or a scientific discipline with at least 15 years of relevant experience, or MS with at least 10 years, or a scientist with a PhD in Pharmaceutical science, Chemical Engineering, or a scientific discipline.
• Lab experience includes research in GMP environment, leadership of technical teams, and project management experience is desirable.
• Computer proficiency in Microsoft Word, Excel, and Outlook and the ability to use enterprise software (examples include: TCU, Trackwise, etc.)
• Strong statistical skills and ability to use standard statistical software (examples include MiniTab, JMP) preferred.

Physical / Safety Requirements:

• Wear all PPE required by EHS (typically safety glasses, lab coat, gloves but may include a respirator).
• Duties may require overtime work, including nights and weekends
• Use of hands and fingers to manipulate office equipment is required
• Position requires sitting for long hours, but may involve walking or standing for periods of time.
• This position requires handling of laboratory chemicals
• Must be able to qualify for 20/25 corrected vision.

In return, you’ll be eligible for[1]:

• Day One Benefits
  • Medical & Dental Coverage
  • Flexible Spending Accounts
  • Life and AD&D Insurance
  • Supplemental Life Insurance
    • Spouse Life Insurance
    • Child Life Insurance
  • 401(k) Retirement Savings Plan with Company Match
  • Time Off Program
    • Paid Holidays
    • Paid Time Off
    • Paid Parental Leave and more
  • Adoption Reimbursement Program
  • Education Assistance Program
  • Employee Assistance Program
  • Community and Volunteer Service Program
  • Employee Ownership Plan
• Additional Benefits
  • Short and Long-Term Disability Insurance
  • Voluntary Insurance Benefits
    • Vision Coverage
    • Accident
    • Critical Illness
    • Hospital Indemnity Insurance
    • Identity Theft Protection
    • Legal and more
  • Onsite Campus Amenities
    • Workout Facility
    • Cafeteria
    • Credit Union

[1] Current benefit offerings are in effect through 12/31/26

Disclaimer

This job description is intended to provide the minimum knowledge, skills and abilities necessary to perform the job.  It may not be inclusive of all the duties and responsibilities of the job.  Simtra reserves the right to make modifications based on business requirements.

Equal Employment Opportunity

Simtra is proud to be an equal opportunity employer. Simtra evaluates qualified applicants without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, protected veteran status, disability/handicap status or any other legally protected characteristic.

Data Privacy

To learn more about Simtra's approach to data privacy, please review the Simtra Recruitment Platform Global Privacy Policy:  https://simtra.com/privacy-policy/

The Role: Research is at the core of WorldQuant. Through rigorous exploration and unconstrained thinking about how to apply data to the financial markets, our researchers are in constant search of new alphas. Researchers at WorldQuant employ tested processes seeking to identify high-quality predictive signals that we believe are undiscovered by the wider market. These signals are mathematical expressions of data that are used as inputs in our quantitative models.

WorldQuant is seeking an exceptional individual to join the firm as a Quantitative Researcher. The person must have a strong understanding of the investment research process to create computer-based models that seek to predict movements of global financial markets. While prior finance experience is not required, a successful candidate must possess a strong interest in learning about finance and global markets. Candidates will have a research scientist mind-set; be a self-starter, a creative and persevering deep thinker who is motivated by unsolved challenges.

WHAT YOU’LL BRING:

• Bachelor's (Hons), Master's or PhD degree in in a highly quantitative or highly analytical field e.g. Math, Physics, Computer Science or Financial Engineering from a leading university with excellent academic records are strongly preferred
• Have a research scientist mindset, i.e., be a deep thinker, creative, persevering, smart, a self-starter, etc.
• Knowledge of Linear Algebra, Statistics, Machine Learning
• Prior experience in Finance/Trading is a plus.
• Be competent in a programming language (Python, Unix)
• Possess good English language skills
• Have a strong interest in learning about worldwide financial markets
• Possess a relentless drive to succeed, supplemented by a strong work ethic

Summary:
Tekion seeks an exceptionally talented and seasoned Senior Staff Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is a seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale. 

Key Responsibilities:

• Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges.
• Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions.
• Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives.
• Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services.
• Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation.
• Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth.
• Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership.
• Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI

Core Competencies & Technical Expertise
The successful candidate will demonstrate mastery in the following areas:

• Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI.
• Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data.
• Deep Learning:
  • Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch.
  • Extensive experience implementing advanced neural network architectures.
  • Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g., spaCy) methodologies.
• Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications.
• Technical Proficiencies:
  • Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous.
  • Proficiency with cloud computing platforms (GCP, Azure, AWS).
  • Expertise in experimental design (A/B testing, causal inference).
  • Proficient in version control systems (Git).

Required Qualifications

• An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field.
• A minimum of 10+ years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value.
• A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach.
• Proven experience in programming, data manipulation, and building models in a business context.
• Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences.

Ideal Candidate Profile

• A profound intellectual curiosity and a systematic, first-principles approach to problem-solving.
• Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable.
• Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred.
• Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences.
• A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams.
• A commitment to continuous personal and team development within a collaborative, high-performance culture.

Address:

Bangalore Office  

Tekion India Private Limited 

6th, 7th & 8th Floor, Helium, Bagmane Solarium City, Doddanekkundi Village, KR Puram Hobli, East Taluk, Bangalore - 560037 

Chennai Office

Embassy Splendid Zone, Block 2, 9th floor, Velan Nagar, Arulmurugan Nagar, Old Pallavaram, Chennai, Tamil Nadu 600043

Role Overview

We are seeking a Principal Applied Scientist to be the highest-level AI technical authority on the team. This role is above the Applied Scientist level — you set the AI research and engineering direction, own the agentic system architecture, define the eval framework standards, and operate as the primary interface to the external AI research community and internal platform AI leadership. You will combine deep research rigor with relentless production focus: every AI capability you design ships, gets measured, and improves based on evidence.

You are the person who answers: "Is this AI approach the right one, and how do we know when it's working"

Key Responsibilities

• Own the agentic system architecture: define the multi-agent coordination patterns, MCP tool taxonomy, intent-to-skill routing logic, policy enforcement design, and memory management strategy across all AI workflows on the platform.
• Lead the AI evaluation framework: design the golden dataset structure, define eval metrics (RAG retrieval quality, scoring accuracy, LLM response correctness, agentic workflow success rate), and own the CI/CD AI eval pipeline that gates every AI capability release.
• Drive the RAG architecture strategy: chunking strategies for MongoDB and Elasticsearch-indexed documents, embedding model selection and fine-tuning, retrieval reranking design, and hallucination mitigation patterns.
• Own the LLM integration architecture: prompt engineering standards, LLM gateway usage policies, context window management, streaming response patterns, and model version governance.
• Lead applied research initiatives: identify novel techniques (RLHF, Constitutional AI, multi-modal, sparse retrieval) that are practically applicable to automotive retail intelligence use cases and prototype them rigorously in Python.
• Define the hexagonal AI adapter contract standard: the formal interface specification between Python AI services and Java domain cores — ensuring AI infrastructure remains swappable without domain logic changes.
• Act as primary technical interface to platform AI leadership (LLM Gateway, ML Platform, Agentic Engine) — influencing platform roadmap based on teams practical requirements.
• Mentor the Applied Scientist and ML Architect; conduct technical reviews of AI system designs, eval frameworks, and research approaches.
• Publish, present, or contribute to open-source where appropriate — representing Tekion's AI engineering excellence externally.

Skills & Qualifications

• 10+ years of applied AI/ML experience with at least 3 years at Staff or Principal level — a track record of shipping AI systems that measurably changed business outcomes.
• Deep expertise across: LLM fine-tuning and alignment, RAG system design (chunking, embedding, retrieval, reranking), agentic frameworks (LangGraph, CrewAI, AutoGen), and MCP tool design.
• Python mastery: PyTorch, Hugging Face Transformers, LangChain/LangGraph, scikit-learn, and production ML serving tooling.
• Strong understanding of distributed AI systems: Elasticsearch-backed vector search, Redis/Aerospike serving, Cosmos DB for AI event logging, and Kafka-based feature pipelines.
• Proven ability to design formal eval frameworks for AI systems — not just accuracy metrics but business aligned quality gates.
• Experience defining and enforcing hexagonal adapter contracts between AI services and domain service layers in production systems.
• Track record of communicating complex AI system design to non-technical stakeholders, influencing product roadmaps, and driving cross-team alignment. 

Good to Have

• Publications or significant open-source contributions in NLP, information retrieval, or agentic systems.
• Experience with Constitutional AI, RLAIF, or preference optimization techniques (DPO, PPO).
• Familiarity with multi-modal AI and its application to automotive retail data (images, documents, tabular data fusion).
• Prior experience in a product-focused AI role at a SaaS or platform company — not purely research. 

Perks & Benefits

• Competitive compensation and generous stock options.
• Medical insurance coverage.
• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies.

Turn Your Expertise Into Impact at Scale

At Interview Kickstart, we don’t just teach—we transform careers. For our lead instructor role, we’re looking for engineers who want to go beyond building systems—to shape the people who build them.

Our practitioner-led approach means every class is taught by experts who’ve built at scale and cleared top hiring bars at FAANG+ companies. With a global learner base, expanding enterprise partnerships, and a fast-growing Agentic AI curriculum, this is a unique opportunity to collaborate with top talent, influence cutting-edge learning, and help define the gold standard for AI education.

Who You Will Be Teaching

Our learners are experienced professionals (5+ years) from software engineering, data science, and related fields, aiming to transition into ML Engineering, Applied Scientist, and AI roles at top-tier companies. They’re highly motivated and technically strong, seeking deep, practical learning—not basics. They value instructors who can connect theory to real-world systems, share insider hiring insights, and provide mentorship rooted in hands-on industry experience.

Key Responsibilities

A. Teaching & Learner Engagement

• Deliver high-impact live sessions on Agentic AI & Machine Learning
• Lead small-group coaching sessions for hands-on problem-solving and doubt resolution
• Run assignment reviews to reinforce concepts and deepen understanding
• Conduct mock interviews (ML System Design, Coding) with actionable feedback
• Provide 1:1 mentorship on career transitions and interview prep
• Host cohort orientations to drive engagement and set expectations

B. Curriculum Development & Review

• Own end-to-end curriculum for Agentic AI/ML (content, assignments, projects)
• Continuously update material with latest tools, trends, and industry practices
• Design evaluation frameworks, rubrics, and assessments
• Collaborate cross-functionally to ensure quality and learner outcomes

C. Marketing & Thought Leadership

• Create masterclasses, webinars, and video content to drive learner growth
• Publish and review technical content (blogs, social, insights)
• Represent IK at events, meetups, and conferences

D. Team Development & Quality

• Mentor and onboard instructors and TAs; set quality benchmarks
• Collaborate to continuously raise teaching standards across the platform
• Leverage learner feedback, ratings, and data to improve delivery quality

What We’re looking for

• 5+ years in Software/ML Engineering (Tier-1 / FAANG+ preferred)
• Strong in DSA, System Design, and ML Systems
• Hands-on experience in Agentic AI / ML (production-level)
• Passion for teaching, mentoring, and driving learner success
• Ability to simplify complex concepts clearly and engagingly
• Strong communication skills and learner empathy

You’d stand out if you have:

• Prior Teaching, mentoring, or content creation experience
• Hiring/interviewing experience at top tech companies
• Research, open-source, or advanced degree in a relevant field
• At the core: a desire to create real impact by shaping careers at scale.

Most Importantly - What’s in it for you?

• Real Impact – Help professionals land top roles and see your impact firsthand
• Shape AI Education – Build and evolve a cutting-edge Agentic AI/ML curriculum
• Remote & Global – Work from anywhere, teach learners worldwide
• Learn From the Best – Collaborate with 700+ instructors from top tech companies
• Top-Tier Pay – Industry-leading compensation with strong growth
• Build Your Brand – Teach, write, and speak on a global stage
• Unlimited Growth – Evolve into leadership and high-impact roles

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Mission

The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.

The impact you will have:

• Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI research to solve customer problems
• Own production rollouts of consumer and internally facing GenAI applications
• Serve as a trusted technical advisor to customers across a variety of domains
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap 

What we look for:

• Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
• Minimum of 5+ years of relevant experience as a Data Scientist preferably working in a consulting role
• Expertise in deploying production-grade GenAI applications, including evaluation and optimizations 
• Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
• Passion for collaboration, life-long learning, and driving business value through AI
• [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets

Tekion seeks an exceptionally talented and seasoned Staff / Lead Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale.  
 
Key Responsibilities 

• Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges. 

• Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions. 

• Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives. 

• Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services. 

• Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation. 

• Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth. 

• Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership. 

• Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI 

Core Competencies & Technical Expertise 

            The successful candidate will demonstrate mastery in the following areas: 

• Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI. 

• Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data. 
   
   

Deep Learning: 

• Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch. 

• Extensive experience implementing advanced neural network architectures. 

• Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g.,spaCy) methodologies. 

• Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications. 

Technical Proficiencies: 

• Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous. 

• Proficiency with cloud computing platforms (GCP, Azure, AWS). 

• Expertise in experimental design (A/B testing, causal inference). 

• Proficient in version control systems (Git). 

Required Qualifications 

• An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field. 

• A minimum of 7 - 9 years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value. 

• A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach. 

• Proven experience in programming, data manipulation, and building models in a business context. 

• Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences. 
   

Ideal Candidate Profile 
 

• A profound intellectual curiosity and a systematic, first-principles approach to problem-solving. 

• Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable. 

• Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred. 

• Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences. 

• A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams. 

• A commitment to continuous personal and team development within a collaborative, high-performance culture. 

Perks and Benefits

• Competitive compensation 

• Generous stock options 

• Medical Insurance coverage 

• Work with some of the brightest minds from Silicon Valley’s most dominant and successful companies 

Technical Expertise:

• Strong background in machine learning, deep learning, and NLP, with proven experience in training and fine-tuning large-scale models (LLMs, transformers, diffusion models, etc.).
• Hands-on expertise with Parameter-Efficient Fine-Tuning (PEFT) approaches such as LoRA, prefix tuning, adapters, and quantization-aware training.
• Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem and good to have distributed training frameworks (e.g., DeepSpeed, PyTorch Lightning, Ray).
• Basic understanding of MLOps best practices, including experiment tracking, model versioning, CI/CD for ML pipelines, and deployment in production environments.
• Experience working with large datasets, feature engineering, and data pipelines, leveraging tools such as Spark, Databricks, or cloud-native ML services (AWS Sagemaker, GCP Vertex AI or Azure ML).
• Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC environments.

Applied Problem-Solving:

• Mandatory skill - Demonstrated success in adapting foundation models to domain-specific applications through fine-tuning or transfer learning.
• Mandatory skill - Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization techniques.
• Experience in working on applied AI problems across NLP, computer vision, or multimodal systems or any other domain.

Leadership & Collaboration:

• (Preferred) Proven ability to lead and mentor a junior applied scientists and ML engineers, providing technical guidance and fostering innovation.
• Strong cross-functional collaboration skills to work with product, engineering, and business stakeholders to deliver impactful AI solutions.
• Ability to translate cutting-edge research into practical, scalable solutions that meet real-world business needs.

Education & Experience:

• 3+ years of hands-on experience in applied machine learning and data science with Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field or appropriate experience.
• Excellent communication and presentation skills to articulate complex ML concepts to both technical and non-technical audiences.
• Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques.

Technical Expertise

• Strong background in machine learning, deep learning, and NLP, with proven experience in training and fine-tuning large-scale models (LLMs, transformers, diffusion models, etc.).
• Hands-on expertise with Parameter-Efficient Fine-Tuning (PEFT) approaches such as LoRA, prefix tuning, adapters, and quantization-aware training.
• Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem and good to have distributed training frameworks (e.g., DeepSpeed, PyTorch Lightning, Ray).
• Basic understanding of MLOps best practices, including experiment tracking, model versioning, CI/CD for ML pipelines, and deployment in production environments.
• Experience working with large datasets, feature engineering, and data pipelines, leveraging tools such as Spark, Databricks, or cloud-native ML services (AWS Sagemaker, GCP Vertex AI or Azure ML).
• Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC environments.
• Applied Problem-Solving

Mandatory skill -

•  Demonstrated success in adapting foundation models to domain-specific applications through fine-tuning or transfer learning.Mandatory skill -
• Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization techniques.
• Experience in working on applied AI problems across NLP, computer vision, or multimodal systems or any other domain.

Leadership & Collaboration

• Proven ability to lead and mentor a team of applied scientists and ML engineers, providing technical guidance and fostering innovation.
• Strong cross-functional collaboration skills to work with product, engineering, and business stakeholders to deliver impactful AI solutions.
• Ability to translate cutting-edge research into practical, scalable solutions that meet real-world business needs.

Other

• Excellent communication and presentation skills to articulate complex ML concepts to both technical and non-technical audiences.
• Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques.

Education & Experience

• Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field.
• 5+ years of hands-on experience in applied machine learning and data science.

Tekion is pioneering the digital transformation of the automotive industry, a sector that has remained largely undisrupted for over five decades. Our flagship platform, the Automotive Retail Cloud™, is the first and fastest cloud-native solution of its kind, fundamentally re-engineering the end-to-end automotive retail experience. By leveraging vast datasets, sophisticated machine learning, and advanced AI, we are creating a seamlessly integrated ecosystem connecting OEMs, retailers, and consumers. We are a globally distributed team of technologists and innovators dedicated to solving complex, high Impact challenges.

The Position

Tekion seeks an exceptionally talented and seasoned Senior Staff Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is a seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale. 

Key Responsibilities

• Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges.
• Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions.
• Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives.
• Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services.
• Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation.
• Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth.
• Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership.
• Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI

Core Competencies & Technical Expertise
The successful candidate will demonstrate mastery in the following areas:

• Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI.
• Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data.
• Deep Learning:
• Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch.
• Extensive experience implementing advanced neural network architectures.
• Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g., spaCy) methodologies.
• Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications.
• Technical Proficiencies:
• Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous.
• Proficiency with cloud computing platforms (GCP, Azure, AWS).
• Expertise in experimental design (A/B testing, causal inference).
• Proficient in version control systems (Git).

Required Qualifications

• An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field.
• A minimum of 11-14 years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value.
• A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach.
• Proven experience in programming, data manipulation, and building models in a business context.
• Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences.

Ideal Candidate Profile

• A profound intellectual curiosity and a systematic, first-principles approach to problem-solving.
• Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable.
• Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred.
• Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences.
• A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams.
• A commitment to continuous personal and team development within a collaborative, high-performance culture.

Perks and Benefits

• Competitive compensation
• Generous stock options
• Medical Insurance coverage
• Work with some of the brightest minds from Silicon Valley’s most dominant and successful companies

Snapshot

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

About Us

The Agents team at Google DeepMind India is driven by the mission of developing foundational capabilities in Large Models towards realizing AGI. We focus on uncovering emergent agentic behaviors through novel reinforcement learning algorithms run at scale.  

We also apply our research advances to Gemini and critical product launches in Google, touching the lives of hundreds of millions of users, and we are looking forward to doing more!

We are seeking a highly motivated and innovative Research Scientist to join our team in Bangalore, focused on advancing the state-of-the-art in autonomous agents  through reinforcement learning and ML optimization methods. You will conduct cutting-edge research on large language models (LLMs), focusing on the development of more capable, robust autonomous agents.

The Role

Research Scientists at Google DeepMind lead our efforts in developing novel algorithmic architecture towards the end goal of solving and building Artificial General Intelligence.

Having pioneered research in the world's leading academic and industrial labs in PhDs, post-docs or professorships, Research Scientists join Google DeepMind to work collaboratively within and across Research fields. They develop solutions to fundamental questions in machine learning and AI.

Key responsibilities:

• Design, implement and evaluate models, agents and software prototypes of large foundational models.
• Push the boundary of state of the art RL methods and machine learning optimization methods to build autonomous agents. 
• Report and present research findings and developments including status and results clearly and efficiently both internally and externally, verbally and in writing.
• Suggest and engage in team collaborations to meet ambitious research goals.
• Work with external collaborators and maintain relationships with relevant research labs and key individuals as appropriate.
• Work in collaboration with our Responsible AI teams to ensure our advances in intelligence are developed ethically and provide broad benefits to humanity.

About You

You are a passionate and talented researcher with a strong foundation and a proven ability to conduct impactful research in AI. You embrace change and thrive under ambiguity. You have a collaborative mindset and are excited to work as part of a team to tackle ambitious research challenges. You are passionate about seeing your research translated into real-world products that improve the lives of users and are eager to work in an environment where research has a direct path to product impact.  You are eager to see your research contribute to real-world applications and are driven by a desire to create positive change through AI.

• PhD in Computer Science, Artificial Intelligence, or a related field.
• Strong publication record in top-tier machine learning conferences or journals.
• Solid understanding of deep learning, natural language processing, computer vision, and/or speech processing.
• Experience with relevant ML frameworks such as JAX, TensorFlow, or PyTorch.

In addition, the following would be an advantage: 

• Experience with multimodal learning, large language models, and/or assistive AI agents.
• Experience with prompt engineering, few-shot learning, post-training techniques, and evaluations.
• Familiarity with large-scale model training and deployment.
• Strong programming skills in Python or similar languages.
• Excellent communication and collaboration skills.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience. 

The Opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries. 

We are proud of: 

• The work we do and the innovation we drive 
• Our values of share, care and dare 
• A workplace culture that fosters creativity, diversity and autonomy 
• Our borderless, global framework, which enables seamless collaboration 

The Role  

As a Senior Data Scientist, you are passionate about experience innovation and eager to push the boundaries of what’s possible. You bring 4+ years of experience, a growth mindset and a drive to make a lasting impact. 

You will thrive in this role if you are: 

• A curious problem solver who challenges the status quo 
• A collaborator who values teamwork and knowledge-sharing 
• Excited by the intersection of technology, creativity and data 
• Experienced in Agile methodologies and consulting (a plus) 

Role & Responsibilities:

Generative AI Innovation & Strategy

• Lead GenAI Initiatives: Spearhead the identification of business scenarios where Generative AI (LLMs, GANs, Diffusion models) can be effectively applied to create tangible value.
• R&D & Prototyping: Research, design, and prototype cutting-edge approaches, exploring existing scientific research to inform solution development.
• Feasibility Analysis: Evaluate the technical and economic feasibility of Generative AI solutions for real-world client use cases.
• Vision Shaping: Collaborate with Product Managers and stakeholders to shape a clear, forward-looking vision of AI technology and its practical applications.

Technical Execution & Implementation

• End-to-End Development: Implement and validate AI solutions for diverse business challenges, writing production-ready code using best engineering practices.
• Optimization: Optimize deep learning models for production environments to ensure scalability and latency requirements are met.
• Cross-Functional Collaboration: Collaborate closely with the ML Engineering team throughout all stages of the lifecycle, from initial research to final implementation.
• Data Strategy: Oversee the data mining process, including data collection, cleansing, and exploratory analysis to support model training and fine-tuning.

Must Have

To be considered for this role, you must meet the following essential qualifications: 

• Total Experience: Minimum of 4+ years in Data Science and Analytics.
• Specialized Experience: Minimum 3+ years focused specifically on developing generative models (LLMs, GANs, VAEs, Diffusion models) and Deep Learning.
• Education: Bachelor’s or Master’s Degree in Computer Science, Mathematics, Applied Statistics, or a related field.

Technical Skills

• Core AI/ML: Expertise in Computer Vision and NLP, with specific experience handling multimodal data (images, text, audio).
• GenAI Stack: Familiarity with Gemini, OpenAI GPT-x, open-source LLMs (Llama, Mistral, etc.), and experience in fine-tuning models (PEFT, LoRA).
• Retrieval-Augmented Generation (RAG): Expertise in designing RAG architectures to ground LLM responses in proprietary data.
• Vector Databases: Proficiency with vector stores such as Pinecone, Milvus, Weaviate, or ChromaDB for efficient semantic search and retrieval.
• Prompt Engineering: Advanced skills in prompt optimization, chain-of-thought reasoning, and framework usage (e.g., LangChain, LlamaIndex).
• Programming: Strong programming skills in Python with proven ability to write clean, production-ready code.
• Frameworks: Proficiency with deep learning frameworks such as PyTorch or TensorFlow.
• Cloud: Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP).

Soft Skills

• Communication: Excellent fluency in English (B2+ or higher) with the ability to explain complex technical concepts to non-technical audiences.
• Problem Solving: A strategic thinker capable of devising holistic solutions for complex customer issues.

Nice to Have (Preferred Qualifications)

• Experience with MLOps tools (e.g., MLflow, Kubeflow) and practices for deploying and monitoring AI models.
• Responsible AI: Knowledge of AI ethics, bias detection, and safety guardrails (e.g., NeMo Guardrails) for deploying LLMs securely.
• API Development: Experience wrapping models in APIs using FastAPI or Flask for integration with frontend applications.
• Knowledge of Reinforcement Learning (RLHF) and self-supervised learning approaches.
• Experience with emerging Generative AI architectures.

If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn. 

Commitment to reaching all kinds of people 

We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all. 

 The Benefits  

This is a Full-Time position based in Bengaluru.

Beyond a competitive compensation package, we offer: 

• Flexibility, with hybrid work options (country-dependent) 
• Learning and development, with access to cutting-edge tools, training and industry experts.

Our benefits are tailored to each location. Your Talent Partner will provide full details during the hiring process. 

Your application process

Once you apply, our Talent Acquisition team will review your application. If your skills and experience align with the role, we’ll reach out for next steps. 

⚠️ Beware of recruitment fraud: Only engage with official Valtech email addresses ending in @valtech.com. 

We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know. 

About Valtech

Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world. 

At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more. 

At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate. 

Are you ready to create what’s next? Join us.