Position Summary

Arcesium seeks an experienced Data Scientist professional to join our Business Operations team within the Client and Partner Development (CPD) organization. The ideal candidate will be comfortable working across large volumes of varied datasets spanning pricing, headcount, market research, commercial performance, and translating that data into the models, frameworks, and insights that drive decision-making. Beyond building models and reporting on data, this person will be expected to draw principled conclusions from their analysis and present clear, strategic recommendations to senior leadership. You will also play an active role in identifying AI-driven solutions that improve how the team works and be a part of AI strategy for CPD. You will collaborate closely with global CPD teams across Sales & Partnership, Revenue Operations, Marketing, Forward Deployed, Account Management and Client Success, Service and Solutions teams to execute complex projects and help the organization scale through data-backed governance.

What you'll do:

• Identify relevant data sources and work with CPD stakeholders across functions to collect, analyze, and interpret large structured and unstructured datasets spanning domains such as pricing, headcount, market research, and operational metrics.
• Devise and apply algorithms and models to extract insight from large data stores. Conduct data and error analysis to improve model performance, and clean and validate data for uniformity and accuracy.
• Analyze data for trends and patterns with clear objectives in mind. Interpret outputs and draw principled conclusions rather than stopping at the analysis itself, ensuring findings inform real decisions.
• Implement analytical models and reporting frameworks end to end, from data ingestion through to leadership-ready outputs.
• Conduct what-if and scenario analyses and translate outputs into clear narratives that are actionable at the senior leadership level.
• Design and develop automation scripts and data pipelines to synthesize and structure data from diverse sources, applying critical thinking to move toward zero-touch processes and maximize end-to-end efficiency.
• Produce KPI dashboards and performance reports using historical data to surface trends and productivity insights for executive audiences, with a focus on telling the story behind the data.
• Act as the primary internal champion for responsible, practical AI use within CPD, educating stakeholders, setting best practices, and ensuring solutions are sustainable and governed.
• Develop reusable AI frameworks, prompt libraries, and automation components that scale adoption across the CPD organization and serve as a foundation for future capabilities.

What you'll need:

• Strong verbal and written communication skills, with the ability to present analytical findings clearly to senior leadership and stakeholders across functions.
• 4 to 7 years of experience in a data analytics or business operations role. Prior experience at a financial technology firm is a plus.
• Advanced proficiency in Excel including complex formulas and VBA Macro programming. Strong Excel fundamentals are a core expectation of this role.
• Proficiency in Python or similar scripting languages for data transformation, automation, and analysis.
• Working knowledge of SQL for querying and managing structured datasets.
• Experience with data visualization tools, particularly Power BI, to build dashboards and reports for executive and operational audiences.
• Experience with data mining and statistical analysis, including segmentation techniques and statistical packages for working with large datasets.
• Proven ability to conduct what-if and scenario analysis and communicate implications clearly to non-technical senior stakeholders.
• Experience tracking KPIs and relevant metrics for revenue organizations, aligned with broader organizational performance indicators.
• Demonstrated hands-on experience building AI-powered workflows, automation pipelines, or LLM-assisted tools in a business context.
• Genuine intellectual curiosity about AI and a track record of applying it to real operational problems.
• Ability to balance medium to long-term analytical projects alongside day-to-day operational responsibilities.

Arcesium's Personal Data Privacy Notice for Candidates is linked here. 

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

About Us

Observe.AI is the AI Agents platform for customer experience, designed to help organizations deliver faster, smarter, and more efficient customer service at scale. The platform enables businesses to deploy specialized AI agents that autonomously execute work across the full CX lifecycle—from handling customer conversations to supporting frontline teams and optimizing operations.

Each AI agent is purpose-built for a specific role, equipped to understand context, make decisions, take action, and continuously improve outcomes. This allows organizations to increase resolution speed, elevate service quality, and reduce operational costs while empowering your frontline team to focus on higher-value work.

Built on a CX-native foundation, Observe.AI helps leading brands like DoorDash, Affordable Care, Signify Health, and Verida improve customer satisfaction, boost agent productivity, and deliver consistent, scalable performance across every customer interaction.

Why Join Us

At our core, we are shaping how AI transforms real-world challenges in the contact center space. As part of our world-class ML team, you’ll work on developing cutting-edge LLM-powered solutions & Agentic AI, building end-to-end processing pipelines, and handling production challenges at scale—millions of interactions daily—while shaping the future of AI-powered contact centers. 

If you are truly an engineer at heart, excited about turning breakthroughs in multi-agent systems, LLMs, NLP, and ML into practical outcomes through applied research, and building scalable production systems to create real product impact, you will feel right at home at Observe.AI. You’ll also have the opportunity to publish in top conferences, and influence Observe.AI’s product and platform strategy. 

Beyond the tech, you’ll join a collaborative, mission-driven culture where innovation, impact, and fun go hand in hand. We value curiosity, collaboration, and the courage to push boundaries.

What you’ll be doing

• Design & develop state-of-the-art LLM-powered AI capabilities and Agentic AI/ Multi-agent systems end-to-end, from ideation to production for Observe.AI’s product offerings, in a fast-paced startup environment.
• Work with cutting-edge tools and technologies in Machine Learning, Deep Learning & Natural Language Processing, including LLMs and LLM-powered technologies/ paradigms, including Agentic AI.
• Build/ maintain highly scalable production systems that power AI capabilities on Observe.AI product/ platform.
• Optimize ML models and processing pipelines for performance, cost-effectiveness, and scale.
• Work with a world-class ML team in building exciting stuff, mentor juniors, and influence peers/ stakeholders.
• Collaborate cross-team with engineers, product managers, customer-facing teams, and customers to understand pain points and business opportunities to build the right solution for the right problem.
• Keep up-to-date with the latest ML/ DL/ NLP literature and influence the technological evolution of Observe.AI platform.
• Contribute to the community through tech blogs and publishing papers in ML/ NLP conferences like EMNLP, ACL, etc.

What you’ll bring to the role

• Bachelor’s or Master’s degree in Computer Science or related disciplines from a top-tier institution with exposure to ML/ DL/ NLP/ NLU.
• An engineering mindset with the competencies of an applied scientist. 
• 3+ years of industry experience in building large-scale NLP/ NLU systems, with recent experience in building LLM-powered applications and Agentic systems.
• Strong understanding of the fundamentals of ML and NLP/ NLU, and practical aspects of building ML systems in production; backed by extensive hands-on experience in building/ scaling customer-facing ML/ NLP/ NLU applications.
• Good understanding of recent advances in building LLM-powered applications,  and multi-agent systems at scale. 
• Excellent implementation skills in Python and Machine Learning Frameworks such as Pytorch, Tensorflow, HuggingFace, etc., and deploying/ maintaining scalable machine learning systems in production.
• Ability to provide thought leadership in one or more technical areas of interest to Observe.AI, and influence product development
• Excellent communication, collaboration skills, and presentation skills.
• Experience with Spoken Language Understanding is a plus
• Published papers in top NLP/ NLU conferences or workshops are a plus
• Relevant open-source contributions are a plus.

Perks & Benefits

• Excellent medical insurance options and free online doctor consultations
• Yearly privilege and sick leaves as per Karnataka S&E Act
• Generous holidays (National and Festive) recognition and parental leave policies
• Learning & Development fund to support your continuous learning journey and professional development
• Fun events to build culture across the organization
• Flexible benefit plans for tax exemptions (i.e. Meal card, PF, etc.)

Our Commitment to Inclusion and Belonging

Observe.AI is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Observe AI does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Observe.AI also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.

We welcome all people. We celebrate diversity of all kinds and are committed to creating an inclusive culture built on a foundation of respect for all individuals. We seek to hire, develop, and retain talented people from all backgrounds. Individuals from non-traditional backgrounds, historically marginalized or underrepresented groups are strongly encouraged to apply.

If you are ambitious, make an impact wherever you go, and you're ready to shape the future of Observe.AI, we encourage you to apply. For more information, visit www.observe.ai.

CSQ326R35

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

This is a hybrid role. At Bluevine, we pride ourselves on our collaborative culture, which we believe is best maintained through in-person interactions and a vibrant office environment. All of our offices have reopened in accordance with local guidelines, and are following a hybrid model. In-office days will be determined by location and discipline.

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

• 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.

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.

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.