About the team

• ML infrastructure: Help build a first-class machine learning platform from the ground up which manages the entire model lifecycle - feature engineering, model training, versioning, deployment, online serving/evaluation, and monitoring prediction quality.
• Data analysis and feature engineering: Apply your expertise to identify and generate features that can be leveraged by multiple use cases and models.
• Model training with batch and real-time prediction scenarios: Use machine learning and statistical modelling techniques such as Decision Trees, Logistic Regression, Neural Networks, Bayesian Analysis and others to develop and evaluate algorithms for improving product/system performance, quality, and accuracy.
• Production operations: Low-level systems debugging, performance measurement, and optimisation on large production clusters.
  Collaboration with cross-functional teams: Partner with product managers, data scientists, and other engineers to deliver impactful solutions.
  Staying ahead of the curve: Continuously learn and adapt to emerging technologies and industry trends.

• Bachelors, Masters, or PhD in Computer Science, Statistics, or a related field.
• Experience in applied machine learning on real use cases (bonus points for ad tech-related use cases). Min 5 years of total experience.
• Great coding skills and strong software development experience (we use Spark, Python, Java).
• Familiarity with real-time evaluation of models with low latency constraints.
• Familiarity with distributed ML frameworks such as Spark-MLlib, TensorFlow, etc.
• Ability to work with large scale computing frameworks, data analysis systems, and modelling environments. Examples include Spark, Hive, NoSQL stores such as Aerospike and ScyllaDB.
• Ad tech background is a plus.
• AI growth mindset / AI Literacy
  
  
  

About the team

Roku pioneered streaming to the TV and continues to innovate and lead the industry. While we are well-positioned to help shape the future of television – including TV advertising – around the world, continued success relies on its investment in our machine learning capabilities. Roku offers millions of options to our users: movies, episodes, news, sports, and channels from all around the world. The Roku Content Platform is key to onboarding content into the Roku ecosystem, delighting our customers. Building a content knowledge platform that provides insights to downstream systems like Search, Recommendations, Ads, and Voice to shape customers' experiences is why we’re actively looking for a Senior Machine Learning / AI Engineer, Content Platform who can drive further innovation.

About the role

Roku pioneered streaming to the TV and continues to innovate and lead the industry. While we are well-positioned to help shape the future of television – including TV advertising – around the world, continued success relies on its investment in our machine learning capabilities.

Roku offers millions of options to our users: movies, shows, news, sports, and channels from all around the world. The Roku Content Platform is key to onboarding content into the Roku ecosystem, delighting our customers. Building a content knowledge platform that provides insights to downstream systems like Search, Recommendations, Ads, and Voice to shape customers' experiences is why we’re actively looking for a Senior Machine Learning / AI Engineering Manager who can drive further innovation.

The person in this role will leverage their technical skills, business intuition, and analytical thinking to build best-in-class machine learning products. This includes integrating Generative AI capabilities and Vision Models to enrich content quality and user engagement. This is a role for a hardened ML practitioner and a highly skilled organizational leader. You will be the architectural and operational bridge between deep AI research and fast-paced product delivery. If you know how to build a 3-year vision for content discovery and translate it into 2-week shipping cycles, this is your team.

What you’ll be doing

• Vision & Strategy: Define the roadmap for ML within the Content Platform..
• Technical Leadership: Provide high-level guidance on model architecture and MLOps infrastructure to ensure models are scalable and production-ready.
• People Management: Lead and grow a high-performing team of ML Engineers. You will be responsible for career development, performance management, and maintaining a culture of rigorous experimentation.
• Cross-Functional Execution: Partner with Product, Engineering, and Content Strategy to align ML initiatives with business goals.
• Delivery: Champion a culture of incremental delivery. Balance long-term R&D with the need to deliver measurable improvements to the production environment.

We’re excited if you have

• 10+ years of total experience in software/ML engineering, with at least 5 years in a dedicated people management leadership role.
• MS or BS in Computer Science, Mathematics, or a related quantitative field.
• You possess a deep theoretical and practical understanding of Machine Learning. 
• You understand the business of streaming and how ML directly impacts the bottom line.
• You can explain complex model to a non-technical executive just as easily as you can debate architecture with a seasoned engineer.
• Proven track record of deploying large-scale ML models into production environments.
• Experience with modern ML stacks (e.g., LLMs, PyTorch, TensorFlow, Spark, and cloud-native MLOps tools).

As a Senior AI/ML Engineer in our AdTech team, you will be a hands-on individual contributor building and deploying machine learning models and AI-driven features for our advertising platform. You will partner with engineering, product, and data science to deliver production-grade ML for campaign optimization, user personalization, and creative intelligence—operating at large scale and low latency across billions of ad events per day. You will contribute to modern ML/LLM capabilities and agentic workflows that automate and enhance campaign operations, with a strong focus on reliability, performance, and measurable business impact.

Key Responsibilities

• Machine Learning Delivery: Design, implement, and ship scalable ML solutions for core AdTech use cases (targeting, ranking, pacing, measurement). Own features end-to-end from experimentation to production rollout.
• ML System Design: Build and evolve the ML lifecycle—data preparation, training, evaluation, and real-time inference—ensuring models integrate cleanly with ad serving systems and meet low-latency, high-throughput requirements.
• Technical Contribution: Contribute to the AI/ML technical roadmap by evaluating tools and techniques (including deep learning, LLMs, and retrieval/feature systems). Make pragmatic trade-offs with an eye toward maintainability and operational excellence.
• AI & Agentic Applications: Develop and integrate LLM-powered features and agentic workflows that assist with campaign workflows such as audience insights, bid/budget recommendations, and creative generation—within well-defined guardrails.
• Cross-Functional Collaboration: Work closely with engineering, product, and data science partners to translate marketing objectives into ML-driven solutions, define success metrics, and deliver iterative improvements.
• Performance & Reliability: Operate ML services in a high-concurrency, latency-sensitive environment. Optimize inference paths, implement monitoring/alerting, manage model drift, and ensure safe deployment practices (A/B testing, canaries, rollbacks).
• Mentorship & Best Practices: Mentor and support other engineers through code/model reviews and knowledge sharing. Champion engineering rigor in testing, observability, documentation, and reproducible ML workflows.

Required Qualifications

• 5+ years of experience in software engineering and/or applied machine learning, with a track record of shipping ML systems to production.
• Experience designing and building high-throughput, low-latency services or data pipelines for large-scale applications.
• Working knowledge of the programmatic advertising ecosystem (DSP/SSP/RTB) is a plus; strong adjacent experience (recommendation, ranking, marketplaces) is also valued.
• Proficiency in at least one of Java, Go, or Python for backend services and ML tooling.
• Hands-on experience with ML frameworks (PyTorch or TensorFlow) and common modeling approaches (classification, ranking, embeddings, deep learning).
• Experience with big data and streaming frameworks (e.g., Spark, Kafka) for processing and analyzing large datasets.
• Experience deploying ML to cloud environments (preferably AWS) and operating services at scale.
• Familiarity with data stores (SQL/NoSQL) such as PostgreSQL/MySQL, Cassandra/DynamoDB, Redis, etc.
• Familiarity with containerization/orchestration (Docker, Kubernetes) and CI/CD practices.
• Strong communication skills and ability to collaborate across disciplines; comfort explaining technical concepts to both technical and non-technical stakeholders.

Preferred Qualifications

• Experience with Large Language Models (LLMs) and generative AI applied to advertising (e.g., ad copy generation, creative optimization, or personalized messaging).
• Experience designing and implementing agentic workflows that support autonomous or semi-autonomous decision-making with strong safety/observability guardrails.
• Experience with model serving and optimization for real-time inference (latency-critical environments).
• Familiarity with modern data lake and table formats (e.g., Apache Iceberg, Apache Hudi) for managing large-scale analytical datasets.
• Knowledge of microservices architecture and event-driven design patterns in distributed systems.
• Contributions to open-source projects, publications, or speaking engagements that demonstrate thought leadership in AI/ML are a plus.

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

Job Title: GenAI Developer/ Engineer

About Us

“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. 

WHY JOIN CAPCO?

You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.

MAKE AN IMPACT

Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.

#BEYOURSELFATWORK

Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.

CAREER ADVANCEMENT

With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.

DIVERSITY & INCLUSION

We believe that diversity of people and perspective gives us a competitive advantage.

Location - Bangalore

Experience - 6 to 10

Skills and Qualifications:

Preferred skills:

Programming: Advanced Python (async programming, OOP, REST APIs, FastAPI, Flask, Pandas, NumPy)

GenAI Frameworks: LangChain, LlamaIndex, Haystack, Semantic Kernel

Machine Learning and AI: Snowflake Cortex, TensorFlow, PyTorch

Key Responsibilities:

• Develop scalable Python applications focused on GenAI
• Knowledge of Snowflake Cortex is a big plus.
• Learn and apply techniques like document chunking and embeddings
• Proficient in both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, Cassandra) databases, including schema design and optimization.
• Design, develop, and fine-tune applications built around foundation models (e.g., LLMs, multimodal models) for specific business needs
• Implement and experiment with generative AI techniques, including but not limited to Retrieval-Augmented Generation (RAG) and prompt engineering
• Lead the implementation of intelligent autonomous agents and multi-agent systems capable of complex decision-making, task execution, and interaction with external systems
• Utilize and contribute to agentic AI frameworks (e.g., LangChain, AutoGen, Semantic Kernel, Crew AI) to build robust and scalable AI agents
• Develop and integrate Model Context Protocol (MCP) solutions to standardize how AI applications access and utilize external data sources, tools, and real-time information
• Lead the development of full-stack applications that integrate generative AI models and agentic systems, ensuring seamless user experiences
• Work with front-end technologies (e.g., React, Angular, Vue.js, JavaScript, TypeScript, HTML, CSS) and back-end frameworks (e.g., Python with Flask/Django/FastAPI, Node.js, Go)
• Design and implement scalable RESTful APIs and microservices to expose AI functionalities
• Deploy, manage, and optimize AI/ML workloads and full-stack applications on at least one major cloud platform (AWS, Azure, or GCP)
• Implement LLMOps/MLOps and DevOps best practices for continuous integration, continuous delivery (CI/CD), model deployment, monitoring, and lifecycle management
• Follow coding best practices and contribute to testing and documentation
• Stay abreast of the latest advancements in generative AI, agentic systems, foundation models, and related fields through continuous research and experimentation
• Collaborate effectively with cross-functional teams, including product managers, data scientists, researchers, and other engineers
• Communicate effectively with both technical and non-technical team members, ensuring alignment and understanding across all project phases.

Company Overview

At CommerceIQ, we help consumer brands accelerate their retail ecommerce market share growth and profitability through machine learning algorithms. We are building the world’s most complete and sophisticated Retail Ecommerce Management Platform, which connects and intelligently automates the management of retail ecommerce channels like Amazon, Walmart, and Instacart, across the entire ecommerce operational chain of retail media management, sales operations, supply chain, and digital self analytics.

We are in hyper growth mode, having recently raised our Series D funding at unicorn valuation (>$1B) and ended our third year of triple-digit revenue growth. Continued acceleration of our growth is fueled by landing new customers, expanding our platform through new products, managing new retail ecommerce platforms, and delivering exceptional customer service to unlock high net retention rates.

What You’ll Be Doing

As a Lead ML Engineer in the Data Science team, you will work closely with the engineering, product, and operations teams to build state-of- the-art ML based solutions for B2B SaaS products. This will entail applying advanced ML algorithms at scale for core products and developing robust end to end production pipelines which includes Human-in-the-Loop component to boost the quality. 

In this role, you will find innovative ways to apply emerging technologies to improve business processes and drive more value for customers. The ideal candidate will have a strong background in machine learning model development, natural language processing and understanding, and data analysis which they can utilize to manage and improve our company’s AI/ML initiatives. 

• Architect and Own multiple AI driven end to end pipelines that allows for deployment and scalability of machine learning models
• Build tools and capabilities that help with data ingestion to feature engineering, data management and organization
• Build tools and capabilities for scalability through distributed optimization 
• Deploy  cutting edge algorithms like LLMs etc. on GPUs at scale
• Work with stakeholders on the research and software engineering side of the company to understand how to support their teams
• Build tools and capabilities for model management and model performance monitoring
• Build operating services at scale with high availability and reliability
• Propose and implement the best engineering practices for scaling ML-powered features, with a goal to enable the fast iteration of and efficient experimentation with novel features
• Contribute and influence the ML infrastructure roadmap in collaboration with Data Science team

What we are looking for -

• Bachelor’s or Masters in Computer Science or Maths/Stats from a reputed college with 5+ years of experience in solving of experience in machine learning engineering problems 
• Experience and understanding of the entire machine learning pipeline from data ingestion to production
• Experience with machine learning operations, software engineering, and architecture
• Experience with large-scale systems including parallel computing and GPUs
• Experience architecting and building an AI pipelines that supports productionization of ML models
• Experience with MLOps systems
• Strong programming skills in a scientific computing language such as Python, SQL
• Experience using frameworks for machine learning and data science like scikit-learn, pandas, NumPy
• Experience working with ML tools such as Tensorflow, Keras, and Pytorch
• Ability to take successful, complex research ideas from experimentation to production
• Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams
• Good depth and breadth in machine learning (theory and practice), optimization methods, data mining, statistics and linear algebra

Why you will love to work with us -

We have multiple brands, which are among the biggest brands operating on amazon, as our customers. You will be responsible for working with their data and developing models and algorithms to drive lift in tune of hundreds of thousands of dollars.

• Opportunity to work on cutting edge technologies in text and images data like LLMs, OCR, transformer based embeddings models
• Deploy code using the most sophisticated tech stack like AWS, GCP etc.
• You will own projects end to end i.e., from exploration to final production
• You will be empowered to make decisions. It implies more responsibilities but high learning
• Immense opportunities to learn and develop ML based SaaS products for brands and get company-wide recognition
• Forget endless meetings. Get things done and start making an impact from day 1
• Work hard, have amazing fun, create history, build the future of eCommerce 
• Start-up environment with a strong culture and values to accelerate your career 

About the Opportunity

The Impact you bring to Cognite

Key Responsibilities

• Take product requirements and independently design, train, test, and deploy ML models (e.g., NLP, Vision-Language Models) for document parsing, layout analysis, and entity matching.
• Write high-quality, scalable production code (Python). Wrap your ML models into robust RESTful or gRPC APIs and integrate them seamlessly into existing industrial master data systems and workflows.
• Implement and maintain CI/CD pipelines for your models. Navigate complex deployment environments, manage containerized applications (Docker/Kubernetes), and optimize inference bottlenecks.
• Work with Principal engineers to translate high-level system architectures into concrete, scalable data pipelines and production-ready microservices.
• Design automated testing for ML pipelines. Monitor deployed models in production for data drift, latency, and accuracy, proactively implementing retraining strategies.
• Collaborate effectively with product managers to define ML capabilities. Provide code reviews and informal technical mentorship to engineers.

Required Skills and Qualifications

• Bachelor’s or Master's degree in Computer Science, Data Science, Software Engineering, or a related field.
• 6–10 years of industry experience in software engineering with a strong focus on machine learning, MLOps, and API development.
• Strong programming skills in Python with experience using backend web frameworks (e.g., FastAPI, Flask, Django) to serve models.
• Solid expertise in frameworks like PyTorch, TensorFlow, Hugging Face Transformers, or LangChain.
• Hands-on experience with containerization (Docker, Kubernetes), Linux environments, CI/CD tools (GitHub Actions, Jenkins), and deploying models on cloud platforms (AWS, Azure, or GCP).
• Solid understanding of software architecture, data structures, and algorithms to ensure performant code.
• Hands-on experience with distributed data processing frameworks (e.g., Apache Spark, Ray, Dask) and orchestrating complex data workflows (e.g., Apache Airflow, Dagster, Prefect).

What Sets your Role Apart

• Independently define the technical ML/SWE approach for ambiguous feature requests and deliver to production.
• Recognize the model is a small part of the solution; expertly manage aspects like API rate limiting, asynchronous processing, and robust data routing around ML components.
• Possess hands-on experience maintaining production ML models and designing resilient systems against poor data quality..

Preferred Qualifications

• Proven experience fine-tuning and deploying multimodal models for visual data and engineering diagrams in live environments.
• Built robust, production-grade RAG pipelines, expertly utilizing Vector/Graph Databases for high-accuracy entity retrieval.
• Familiar with orchestrating multi-step reasoning using frameworks like LangGraph or AutoGen for real-world problem-solving.
• Strong understanding of advanced OCR, layout parsing, and techniques for consistent structured JSON extraction from complex industrial PDFs. Manufacturing/OT dataset experience preferred.
• Ability to optimize LLMs/VLMs for inference latency (quantization, TensorRT, vLLM), potentially in constrained, on-premises environments.
• Experience with modern data lake/lakehouse architectures (Delta Lake, Iceberg, Databricks) for efficient querying and preprocessing of petabyte-scale unstructured data for LLM/VLM training and RAG.

 

 

 

Learn more about us

 

 

 

• Impact 2025
• Cognite's Industrial AI: Moonshot
• We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.

 

 

Equal Opportunity

Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.

Staff Data Scientist – Supply Chain AI (Small Language Models)  

At Avathon, we build AI products that solve real industrial problems at scale. We believe the future of enterprise AI lies in small, focused, high-performance models—deeply grounded in domain context—not just large, generic systems. 

We’re looking for an experienced Data Scientist to join our Supply Chain AI team in India. In this role, you’ll design, fine-tune, and deploy optimized Small Language Models (SLMs) that power production-grade AI features across logistics, planning, inventory, and demand forecasting. 

What Makes This Role Unique 

This is a product-first data science role. You won’t just build models—you’ll own how they show up in real products used by large enterprises. Your work becomes the intelligence layer that sits on top of our graph and indexing systems and directly drives customer outcomes. 

What You’ll Do 

• Build and fine-tune SLMs/LLMs for production use cases such as semantic search, forecasting, contract intelligence, and conversational insights. Optimize models for performance, cost, and latency using PEFT, quantization, and efficient inference techniques 

• Embed supply chain knowledge into models by working closely with domain experts and product teams 

• Enable agentic workflows, allowing AI Assistants to execute planning, optimization, and decision-support tasks 

• Integrate models into products using custom Lambdas, and a Graph-based microservices architecture  

• Apply vector search and semantic reasoning to help customers navigate complex supply chain relationships 

• Work with real enterprise data—ERP, logistics, inventory, supplier, and contract datasets 

• Deploy and operate models using strong MLOps practices on platforms like AWS, GCP or AZURE 

• Measure and improve quality, reducing hallucinations and improving reliability through continuous evaluation 
• Partner with engineering, product, and operations teams to ship impactful AI features end-to-end 

What We’re Looking For 

• Experience working with SLMs (Mistral, Phi, Nemotron, Llama variants), applying parameter-efficient fine-tuning (LoRA/QLoRA) to optimize task-specific natural language query answering with high accuracy and minimized hallucinations. 

• Strong understanding of supply chain data and workflows (logistics, inventory, procurement, ERP systems) 

• Familiarity with Knowledge Graphs and graph-based data modeling, including designing and querying Neo4j graphs for relationship-driven insights. 

• Solid hands-on skills in Python, PyTorch/TensorFlow, GraphQL, and vector databases 

• 8+ years of experience in forecasting, optimization, supply chain analytics, or AI-driven products 

• Experience designing Retrieval-Augmented Generation pipelines using document chunking, metadata filtering, hybrid (dense + sparse) retrieval, and SLM/LLM grounding for enterprise knowledge search. 

• Hands-on experience building and tuning FAISS-based vector indexes (IVF, HNSW, PQ) for large-scale semantic similarity search with low-latency production deployment 

• Experience taking models from prototype to production 

• Bonus: reinforcement learning, MARL, graph neural networks, or probabilistic modeling 

• Clear communication skills and a strong sense of product ownership 

Why Avathon 

You’ll work on core AI products, not experiments—solving complex supply chain problems for global enterprises, while building from India as a key innovation hub. 

If you enjoy shipping AI that delivers measurable business value, this role is for you. 

Solutions Architect

Role Overview 

As Solutions Architect you operate at the intersection of deep technical leadership and high-stakes client engagement. You will: 

• Own solution architecture and technical delivery for marquee customers, ensuring JazzX’s AGI platform unlocks measurable business value. 
• Guide multi-disciplinary squads (product, research, engineering, and customer success) from discovery through full production rollout. 
• Shape platform roadmap with field feedback, driving features that accelerate time-to-value and differentiate JazzX in the market. 

You are equally comfortable white-boarding LLM retrieval strategies, optimising prompt chains, troubleshooting Kubernetes deployments, or presenting to a C-suite audience. 

Key Responsibilities 

Qualifications 

Must-Have 

• 10–12 years of software engineering experience, 5+ in staff/principal or solution-architect roles. 
• Proven record delivering large-scale, low-latency distributed systems (Python, Java, Go, or C++). 
• Hands-on with LLM / AI frameworks (LangChain, LlamaIndex, PyTorch, TensorFlow) and productionising ML pipelines. 
• Expertise integrating REST/GraphQL APIs, streaming platforms (Kafka), SQL & NoSQL stores, and vector DBs. 
• Outstanding client-facing communication, executive-level presentation, and stakeholder-management skills. 

Nice-to-Have 

• Masters or PhD in AI/Data Science/Computer Science 
• Experience shipping RAG or agent-based AI systems in regulated industries. 
• Nice to have certifications in cloud architecture, data engineering, or security (e.g., AWS SA-Pro, CKA). 
• Background in professional-services, forward-deployed engineering, or AI platform product management. 

Attributes 

• Empathy & Ownership: You listen carefully to user needs and take full ownership of delivering great experiences. 
• Startup Mentality: You move fast, learn quickly, and are comfortable wearing many hats. 
• Detail-Oriented: You care about the little things  
• Mission-Driven: You want to solve important, high-impact problems that matter to real people. 
• Team-Oriented: Low ego, collaborative, and excited to build alongside highly capable engineers, designers, and domain experts.  

Travel:

This position requires the ability to travel to client sites as needed for on-site deployments and collaboration. Travel is estimated at approximately 30–40% of the time (varying by project), and flexibility is expected to accommodate key client engagement activities. 

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 THE ROLE

You are a seasoned Data Scientist, passionate about building robust, real-time machine learning solutions to combat financial crime. Working within the Risk & Fraud Team, you will leverage advanced statistical modeling and machine learning to detect, prevent, and adapt to evolving fraud threats. You thrive on solving complex problems with highly imbalanced data and delivering tangible risk reduction impact in a fast-paced environment.

You strongly believe in agile principles and use them to deliver value incrementally. You are eager to learn about new methodologies and practices and apply them directly in your work.

As a Senior Data Scientist you’ll be:

• Model Development & Risk Mitigation: Design, develop, and implement advanced ML/Statistical models to predict and prevent various fraud typologies. Focus on driving impact by optimising costs and reducing risk using ML/Stats models.
• Specialised Data Handling: Employ advanced techniques to manage and model highly imbalanced, large datasets characteristic of the fraud domain.
• Adaptive Systems: Build and maintain models that can quickly adapt to new and evolving fraud typologies and emerging threats.
• Real-Time MLOps: Develop, optimise, and deploy ML models for real-time/low-latency inference in production settings.
• Data & Feature Engineering: Utilize, enrich, and contribute to the feature store ecosystem, ensuring high-quality, scalable features for risk models.
• Performance Monitoring: Implement and maintain robust drift monitoring and model performance tracking to ensure deployed models remain effective and stable.
• Collaboration: Work closely with ML Engineers to productionize models leveraging AWS/GCP tech stack, and collaborate with Business and Product teams to understand requirements and solutionise data products.
• Exploration: Identify creative solutions in order to build relevant training data sets and explore the value of new data structures like knowledge graphs for relational fraud detection.

WHAT ARE WE LOOKING FOR

• You have 6+ years of experience in Software Development or Machine Learning, with a strong emphasis on practical model development and deployment.
• You are Strong in Python and have expert knowledge with Machine Learning tools/libraries (e.g., scikit-learn, statmodels, TensorFlow, Keras, or PyTorch).
• You have experience with big-data technologies such as Spark, SparkML, Hadoop etc. and have handled large data in a distributed processing environment. AWS, GCP, or Azure (anyone) cloud knowledge is preferred.
• You are proficient in ML training, optimising, feature selection and engineering, hyperparameter tuning and have knowledge about trade-offs in using different algorithms.
• You have demonstrated experience in developing and deploying a variety of ML-algorithms (e.g., logistic regressions, boosted trees, neural networks) that work in real-time settings.
• You have a good working knowledge with basic data table operations (SQL etc.), and data transform in the warehouse (dbt etc.).
• You are comfortable with ambiguity and are a self-starter—you take initiative in spotting opportunities and finding ways to solve challenges with data.
• Familiarity with Financial Services and Fintech space is preferred.
• You will be helping optimise all aspects of our sales funnel including finding ways to increase lead quality, reduce our cost of acquisition, optimise lead allocation, and improve the likelihood of successful lending outcomes for our members

Highly Desirable Skills:

• Exposure to Cost-Sensitive Learning techniques, where the economic impact of prediction errors is a key optimization factor.
• A decent idea and practical exposure to MLOps principles (e.g., model versioning, continuous integration/deployment for ML).
• Experience with Drift monitoring tools and frameworks.
• Exposure to Knowledge Graphs or graph database applications.

• Competitive Compensation -  competitive salary and share options
• Time Off – Generous annual leave on top of bank holidays.
• Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
• Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.
• Health Insurance – Private family insurance with additional OPD coverage and top-up options.
• Life & Accident Cover – Comprehensive accidental and life insurance protection.
• Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.
• Volunteering & Development Days – Paid days annually for volunteering or personal growth.
• Learning & Development – Annual budget for books, courses, coaching, and more.
• WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.
• Home Office Setup – Contribution towards setting up your home office
• Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
• Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent).

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

Staff Software Development Engineer  

As a Staff Software Development Engineer at JazzX AI, you'll define the technical vision for our enterprise AI platform, mentor senior engineers, and oversee the design, development, and deployment of critical AI, software and infra services and components.  You'll be responsible for ensuring the platform's scalability, reliability, security and observability. 

What You Will Do 

Design and Architect Scalable Solutions: 

• Lead the design and development of high-performance, scalable services and components for our enterprise AI platform using a cloud-first, cloud-agnostic approach with world class AI capabilities, scalability, security, privacy and operability.
• Champion a cloud-first, cloud-agnostic approach to ensure platform versatility, scalability, and future-proof architecture.
• Champion innovative AI and software design patterns and best practices to ensure code maintainability, reusability, and testability.
• Contribute to the platform's technical direction by staying up to date on emerging AI technologies, cloud design patterns and user experience methodologies. 

Collaborative Innovation: 

• Foster a collaborative environment by working closely with cross-functional teams (AI/research engineers, software engineers, architects, product managers, and designers) to translate complex platform and product requirements into elegant, scalable, and modular AI, software and infrastructure components.
• Foster a collaborative and inclusive environment by effectively communicating technical concepts and design decisions across diverse audiences.
• Provide mentorship and guidance to junior engineers, fostering their growth and development. 

Driving Operational Excellence: 

• Oversee the seamless integration of components into the platform, ensuring efficient operation, reliability, and a dependable user experience for both customers and partners.
• Champion DevOps and AIOps best practices for AI services, maintainability, performance optimization, and observability. 

Requirements 

• Minimum 10+ years of experience designing, building, and operating cloud-native applications at scale. Expertise in container orchestration frameworks like Kubernetes and containerization technologies like Docker. Expertise in AI/ML/data capabilities, platforms, frameworks and tools.
• Proven track record deploying and managing cloud environments using Infrastructure as Code (IaC) tools like Terraform, Ansible, or CloudFormation.
• Experience in designing and implementing highly available, scalable, and fault-tolerant systems. 

Development Lifecycle: 

• End-to-end ownership of the entire software development lifecycle (SDLC) for complex enterprise platforms and products. This includes experience in design, prototyping, development (including unit, integration, and end-to-end testing), deployment, and ongoing operations. 

Technical Skills: 

• Mastery of essential software development principles with a focus on clean code, design patterns, and best practices.
• In-depth expertise in at least two of the following programming languages: Python, Java, JavaScript, Golang, or C++.
• Solid understanding of distributed systems concepts and experience with distributed tracing tools. 

AI/ML Experience: 

• Demonstrated experience in building, deploying, and managing Machine Learning (ML) and Artificial Intelligence (AI) platforms and services. Familiarity with MLOps practices, frameworks (TensorFlow, PyTorch), and tools is a plus 
• Familiarity with modern LLMs and AI agent frameworks like LangChain, LlamaIndex , AutoGen etc. is a strong plus 

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.

About The Role

As a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.

You will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.

Responsibilities 

• Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms.
• Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system.
• Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system.
• Using mathematical models and analysis to measure the software performance and inform design decisions.
• Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries.
• Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks.
• Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.

Skills & Qualifications 

• Bachelor’s, Master’s, PhD, or foreign equivalent in Computer Science, Computer Engineering, Mathematics, or a related field. 
• Proven experience leading technical teams, including mentoring engineers, setting technical direction, and driving execution. 
• Strong understanding of hardware architecture concepts and willingness to dive into new system architectures. 
• Proficiency in C++ and Python; experience with low-level systems programming. 
• Familiarity with library/API development best practices and performance optimization. 
• Excellent debugging skills across complex, layered software stacks. 

Preferred Skills & Qualifications 

• Experience leading teams in kernel development, performance optimization, or low-level systems programming. 
• Strong background in parallel algorithms and distributed memory systems. 
• Hands-on experience with accelerators such as GPUs, FPGAs, or other custom hardware. 
• Familiarity with machine learning workloads and frameworks like TensorFlow and PyTorch. 
• Understanding of HPC kernels and strategies for optimizing them on modern architectures.

Position Overview

We are seeking a Computer Vision AI & ML Engineer to design, build, and deploy advanced perception systems for real-world robotics and automation. You will work across the full machine learning lifecycle—model development, data strategy, evaluation, and production integration—to deliver robust, high-performance vision capabilities. This role combines applied research with hands-on engineering and offers the opportunity to influence both architecture and roadmap decisions.

Responsibilities

• Develop and optimize deep learning models for object detection, segmentation, tracking, and 3D scene understanding using multi-modal sensor data.
• Build scalable pipelines for data processing, training, evaluation, and deployment into real-world and real-time systems.
• Design labeling strategies and tooling for automated annotation, QA workflows, dataset management, augmentation, and versioning.
• Implement monitoring and reliability frameworks, including uncertainty estimation, failure detection, and automated performance reporting.
• Conduct proof-of-concept experiments to evaluate new algorithms and perception techniques; translate research insights into practical prototypes.
• Collaborate with robotics, systems, and simulation teams to integrate perception models into production pipelines and improve end-to-end performance.

Preferred Qualifications

• Strong experience with deep learning frameworks (PyTorch, TensorFlow, or JAX).
• Background in computer vision tasks such as detection, segmentation, tracking, or 3D scene understanding.
• Proficiency in Python; familiarity with C++ is a plus.
• Experience building training pipelines, evaluation frameworks, and ML deployment workflows.
• Knowledge of 3D geometry, sensor processing, or multi-sensor fusion (RGB-D, LiDAR, stereo).
• Experience with data annotation tools, dataset management, and augmentation techniques.
• Familiarity with robotics, simulation environments (Isaac Sim, Gazebo, Blender), or real-time systems.
• Understanding of uncertainty modeling, reliability engineering, or ML monitoring/MLOps practices.

Position Overview

We are looking for a Software Engineer to work at the forefront of developing and optimizing the software infrastructure and tools necessary for training cutting-edge AI models. You will focus on building robust, scalable, and efficient training pipelines and frameworks that support the entire machine learning lifecycle, from data preparation to model deployment. You will collaborate with researchers and machine learning engineers to ensure seamless integration and operation of training systems, pushing the boundaries of what AI can achieve in real-world robotics applications. You will explore new ways to efficiently make use of many types of data in our training pipeline.

Responsibilities

• Develop and maintain robust, scalable, and distributed training pipelines (data preprocessing, training orchestration, and model evaluation) and frameworks for large-scale AI models.
• Optimize training processes for performance and resource utilization, ensuring scalability and reliability.
• Collaborate with researchers and machine learning engineers to integrate state-of-the-art algorithms and techniques into training pipelines.
• Monitor and analyze training, identifying bottlenecks and proposing solutions to improve efficiency and performance.
• Ensure the robustness and reliability of the training infrastructure, including automated testing and continuous integration.

Preferred Qualifications

• BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
• Minimum of 3 years of industry experience.
• Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
• Strong background in distributed computing, parallel processing techniques, handling large-scale datasets and data preprocessing.
• Deep understanding of state-of-the-art machine learning techniques and models.
• Experience with cloud-based training environments (AWS, Google Cloud, Azure).
• Experience in developing and maintaining software tooling and infrastructure for machine learning.
• Deep understanding and practical experience with software engineering principles, including algorithms, data structures, and system design.
• Experience with continuous integration and automated testing frameworks.

Position Overview

We are looking for a Software Engineer to work at the forefront of deploying our cutting-edge AI models, enhancing the performance and capabilities of our embodied systems. You will be responsible for optimizing AI inference processes from lightweight to billion-parameter models, ensuring our robots operate with unmatched efficiency and intelligence in real-world environments. You will work at the intersection of systems and machine learning, directly contributing to making our AI models more powerful and adaptive by ensuring consistent performance in light of variable and perhaps unforeseen compute and hardware constraints.

Responsibilities

• Develop and optimize runtime AI inference pipelines for real-world robotic deployment.
• Build infrastructure, frameworks, and tooling to enable reliable integration of models into robotic systems and informative analysis of production models to drive the direction of architecture choice and deployment system design.
• Formulate specialized optimization solutions for various inference paradigms and scenarios (autoregressive models, denoising models, hierarchical models, state machines, multi-agent systems, cloud-based inference).
• Adapt optimization solutions to various compute, hardware, and networking constraints.

Preferred Qualifications

• BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
• Minimum of 3 years of industry experience.
• Proficiency developing in low-level systems languages (C, C++, Rust, Go), Python and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
• Deep understanding and practical experience with low-level systems concepts (multithreading, networking, embedded systems, memory management).
• Experience with CUDA.
• Deep understanding of state-of-the-art machine learning techniques and models.
• Experience optimizing various machine learning architectures.
• Experience with machine learning compilers.
• Experience optimizing model inference for robotic systems deployment.

Position Overview

We are seeking a versatile Robotics Engineer to develop and implement software solutions for our manipulation systems. The ideal candidate will have experience in controls, perception, and planning. You will be working on deploying state-of-the-art learning-based algorithms on real robot setups, focused on daily manipulation tasks. This role will require close collaboration with researchers and the ML team. The ideal candidate should be comfortable with building high-quality software for robotic manipulation and deploying it on robot hardware.

Responsibilities

• Help design algorithms, models, and techniques for various robotic manipulation tasks.
• Design hardware and software systems for various robotic manipulation tasks.
• Write controllers and perception stacks for real-world robotic deployment.
• Write and maintain production-level C++ and Python code for our robotic manipulation platforms.
• Collaborate with machine learning engineers to deploy state-of-the-art models on our robots.
• Continuously improve and optimize robotic software for performance, reliability, and scalability.

Preferred Qualifications

• BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
• Experience in designing robotic manipulation systems and deploying software on real robots.
• Experience with writing controllers and knowledge of robotics (e.g., kinematics, dynamics, control, motion planning, SLAM).
• Proficiency in Python and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
• Systems-level understanding of the various software modules and their interfaces in a robotic application (ROS/ROS2, simulators, etc.).
• Publications at top-tier ML, robotics or CV conferences (e.g., NeurIPS, ICML, ICLR, CoRL, RSS, ICRA, CVPR, ECCV, ICCV).
• Experience with designing custom robot hardware solutions.
• Proficiency with various robot learning techniques (RL, imitation learning, etc.).
• Experience working with modern computer vision algorithms, sensors (LiDAR, camera, radar, etc.), 3D (meshes, point clouds, etc.), segmentation, tracking, object detection.

Senior Staff Engineer

As a Senior Staff Engineer at JazzX AI, you will operate as a strategic technical leader—driving platform architecture, guiding critical projects, and influencing product direction.  You will serve as a hands-on contributor, provide technical mentorship across teams, and partner with senior stakeholders to ensure our solutions are innovative, robust, and aligned with the company’s long-term vision. You will also be instrumental in fostering a high-performance engineering culture that emphasizes collaboration, excellence, and continuous improvement. 

Key Responsibilities 

Technical Leadership & Architecture 

• Define and evolve JazzX.ai’s technical strategy, ensuring our AI-driven systems can scale and adapt to future challenges.
• Own the end-to-end architecture for key platform components, ensuring high levels of reliability, security, and performance.
• Evaluate emerging technologies, tools, and frameworks, making data-driven recommendations that influence company-wide engineering decisions. 

Project Execution & Cross-Functional Collaboration 

• Lead complex, high-impact engineering initiatives that require coordination across multiple product and infrastructure teams.
• Collaborate with Product Management, AI research engineering, , and UX to scope technical requirements and deliver solutions that align with business objectives.
• Serve as a trusted advisor to senior stakeholders, clearly communicating technical roadmaps, trade-offs, and risks. 

Mentorship & Team Development 

• Guide and mentor engineers at all levels, from early-career to senior staff, providing technical direction and career development support.
• Champion best practices in code quality, architecture reviews, testing, and documentation.
• Foster an inclusive and innovative engineering culture, encouraging knowledge-sharing and continuous learning. 

Innovation & AI Integration 

• Partner with the AI research engineering team team to design and implement modern AI frameworks and capabilities  as production services in the platform
• Drive the exploration and adoption of state-of-the-art AI/ML technologies to keep JazzX.ai ahead of industry trends.
• Identify strategic opportunities where AI can deliver enhanced functionality or novel capabilities for our platform. 

Operational Excellence 

• Define and enforce SLAs for mission-critical services, ensuring minimal downtime and fast recovery.
• Champion DevOps best practices around CI/CD, cloud infrastructure, observability, and security.
• Collaborate with Site Reliability Engineers (SREs) and Security teams to optimize performance and maintain compliance with industry standards. 

 Qualifications 

Educational Background 

• Bachelor’s or Master’s in Computer Science, Engineering, or a related field; or equivalent experience. 

Experience & Technical Expertise 

• 10–12+ years of professional software engineering experience, with at least 5 years in technical leadership roles (Principal, Staff, or equivalent).
• Proven track record leading complex, large-scale projects across distributed systems, backend architecture, or cloud platforms.
• Deep expertise in at least one or more programming languages (e.g., Python, Java, Javascript, Go,  C++), with a willingness to learn new technologies.
• Strong understanding of microservices, event-driven architectures, and container orchestration tools (Kubernetes, Docker).
• Experience with large-scale data processing, streaming platforms (e.g., Kafka), and databases (both SQL and NoSQL).
• Familiarity with AI/ML frameworks (TensorFlow, PyTorch) and operationalizing machine learning solutions is a plus. 

AI/ML Experience: 

• Demonstrated experience in designing, building, deploying, and managing Machine Learning (ML) and Artificial Intelligence (AI) platforms and services. Hands on experience with MLOps practices, frameworks (TensorFlow, PyTorch), and tools. 
• Experience building platforms and applications with modern LLMs and AI agent frameworks like LangChain, LlamaIndex , AutoGen etc. is a strong plus 

Leadership & Soft Skills 

• Exceptional communication and presentation skills, with the ability to influence technical and non-technical stakeholders at executive levels.
• Proven ability to mentor, coach, and inspire engineers, build high-performing teams and a culture of engineering excellence.
• Experience navigating ambiguous requirements and delivering results in a fast-paced, startup environment.
• Demonstrated thought leadership in architectural design, code quality, and technical strategy. 

Staff Software Development Engineer  

As a Staff Software Development Engineer at JazzX AI, you'll define the technical vision for our enterprise AI platform, mentor senior engineers, and oversee the design, development, and deployment of critical AI, software and infra services and components.  You'll be responsible for ensuring the platform's scalability, reliability, security and observability. 

What You Will Do 

Design and Architect Scalable Solutions: 

• Lead the design and development of high-performance, scalable services and components for our enterprise AI platform using a cloud-first, cloud-agnostic approach with world class AI capabilities, scalability, security, privacy and operability.
• Champion a cloud-first, cloud-agnostic approach to ensure platform versatility, scalability, and future-proof architecture.
• Champion innovative AI and software design patterns and best practices to ensure code maintainability, reusability, and testability.
• Contribute to the platform's technical direction by staying up to date on emerging AI technologies, cloud design patterns and user experience methodologies. 

Collaborative Innovation: 

• Foster a collaborative environment by working closely with cross-functional teams (AI/research engineers, software engineers, architects, product managers, and designers) to translate complex platform and product requirements into elegant, scalable, and modular AI, software and infrastructure components.
• Foster a collaborative and inclusive environment by effectively communicating technical concepts and design decisions across diverse audiences.
• Provide mentorship and guidance to junior engineers, fostering their growth and development. 

Driving Operational Excellence: 

• Oversee the seamless integration of components into the platform, ensuring efficient operation, reliability, and a dependable user experience for both customers and partners.
• Champion DevOps and AIOps best practices for AI services, maintainability, performance optimization, and observability. 

Requirements 

• Minimum 8+ years of experience designing, building, and operating cloud-native applications at scale. Expertise in container orchestration frameworks like Kubernetes and containerization technologies like Docker. Expertise in AI/ML/data capabilities, platforms, frameworks and tools.
• Proven track record deploying and managing cloud environments using Infrastructure as Code (IaC) tools like Terraform, Ansible, or CloudFormation.
• Experience in designing and implementing highly available, scalable, and fault-tolerant systems. 

Development Lifecycle: 

• End-to-end ownership of the entire software development lifecycle (SDLC) for complex enterprise platforms and products. This includes experience in design, prototyping, development (including unit, integration, and end-to-end testing), deployment, and ongoing operations. 

Technical Skills: 

• Mastery of essential software development principles with a focus on clean code, design patterns, and best practices.
• In-depth expertise in at least two of the following programming languages: Python, Java, JavaScript, Golang, or C++.
• Solid understanding of distributed systems concepts and experience with distributed tracing tools. 

AI/ML Experience: 

• Demonstrated experience in building, deploying, and managing Machine Learning (ML) and Artificial Intelligence (AI) platforms and services. Familiarity with MLOps practices, frameworks (TensorFlow, PyTorch), and tools is a plus 
• Familiarity with modern LLMs and AI agent frameworks like LangChain, LlamaIndex , AutoGen etc. is a strong plus 

We are seeking an experienced and highly skilled Senior Data Scientist to lead our efforts in optimizing ad display on native Android surfaces. In this role, you will design and implement data-driven strategies to maximize ad effectiveness, user engagement, and revenue. You will collaborate closely with product managers, engineers, and cross-functional teams to drive innovation, improve ad relevance, and ensure a seamless user experience.

As a Senior Data Scientist, you’ll get to:

• Develop and refine data-driven ad optimization strategies tailored to native Android environments, focusing on user engagement, personalization, and revenue uplift.
• Design, implement, and improve predictive models for ad targeting, recommendation, and bidding strategies using cutting-edge machine learning and statistical techniques.
• Lead the design and analysis of experiments to test ad placements, formats, and targeting methods. Use data from A/B tests and multivariate testing to validate hypotheses and inform decisions.
• Analyze user behavior patterns to understand engagement and dropout points, leveraging insights to optimize ad positioning, timing, and relevance.
• Partner with product managers, engineers, designers, and marketing teams to align ad strategies with business objectives and user experience goals. Communicate insights and recommendations effectively to both technical and non-technical stakeholders.
• Ensure the scalability of ad models across a wide range of Android devices and varying network conditions. Work closely with engineering teams to deploy and monitor models in a production environment.
• Provide mentorship and guidance to junior data scientists, fostering a collaborative and innovative team environment. Lead by example in developing high-quality, scalable solutions for complex ad optimization challenges.

You’ll be a good fit if you have:

• PhD (preferred) or Master's Degree (required) in Computer Science, Data Science, Statistics, Machine Learning, or a related field.
• 6+ years of experience in data science or machine learning, with a strong focus on ad technology or user experience optimization.
• Demonstrable experience in working with ad serving, ad tech stacks, and optimization techniques, especially within Android or mobile ecosystems.
• Expertise in machine learning frameworks (TensorFlow, PyTorch, or similar).
• Advanced proficiency in Python, or Kotlin.
• Experience with data processing and pipeline tools (e.g., Spark, Hadoop, Airflow).
• Deep understanding of A/B testing, causal inference, and other experimentation methods.
• Familiarity with ad tech, programmatic advertising, and user behavior metrics, particularly in the context of mobile and Android platforms.
• Excellent analytical, problem-solving, and communication skills. Proven ability to articulate complex data science concepts to stakeholders across different domains.

 Nice to have: 

• Previous experience optimizing ad displays on native mobile or Android surfaces.
• Familiarity with the Android SDK and understanding of native Android UI/UX design principles.
• Knowledge of reinforcement learning, multi-armed bandit models, and contextual targeting techniques.

This role is based at our Bengaluru, India office and follows a Hybrid schedule that will be aligned with our Return to Office guidelines.

About Nanonets

Nanonets has a vision to help computers see the world starting with reading and understanding documents.Machine Learning (ML) is no longer a futuristic concept—it's a present-day powerhouse transforming the business landscape. Nanonets is at the forefront of this transformation, offering innovative ML solutions designed to make document related processes faster than ever before. 

From automating data extraction processes to enhancing reconciliation, our solutions are designed to revolutionize workflows, optimize operations, and unlock untapped potential for our clients. Our client footprint spans across brands such as Toyota, Boston Scientific, Bill.com and Entergy to name a few enabling businesses across a myriad of industries to unlock the potential of their visual and textual data

We recently announced a series B round of $29 million in funding by Accel and are backed by the likes of existing investors including Elevation Capital & YCombinator. This infusion of capital underscores our commitment to driving innovation and expanding our reach in delivering cutting-edge AI solutions to businesses worldwide.

We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity.

About the Role

As a senior fullstack engineer, you should be comfortable with both backend (Preferably Golang) and frontend (Preferably React). You will be primarily working on architecting and shipping new backend features like new integrations, enabling more machine learning API’s, building complex workflows & various growth hacking efforts. You will also work on optimizing response times, building features that will scale to 100’s of millions of documents we process every month.

What we expect from you

• Agility in shipping features
• Good at code design and architecture
• Great communication
• Backend experience - Preferably golang, python
• Databases - Understanding of data modeling for Nosql preferably cassandra.
• Strong fundamentals in OOP design patterns.
• Basic understanding of Devops.
• Curiosity and Willingness to learn new things while solving a challenging problem.
• Learning and incorporating best practices in software development, security and design/architecture.

What We're Looking For:

• B.E/B.Tech preferable from a Tier 1 college
• 3-8 yrs in software development with a strong foundation in software architecture and design as well one of frontend and backend development
• Proficiency in programming and development technologies.
• Strong familiarity with DevOps best practices and tools.
• Innovative mindset and a passion for driving engineering excellence.

Some of the interesting features we have shipped in backend

• Compile python code into C which could be imported into golang and then shipped as binary for on premise systems
• Autoscale GPU dependent services with kubernetes with a custom metric
• Displaying machine learning metrics in simplified ways to end users so they can act based on those metrics
• Building large number and variety of integrations with relatively generic interface like salesforce, quickbooks, RPA's, external databases
• Process large number of files in highly distributed manner in golang
• Intelligent lookups leveraging vector databases with data synced from ERP Systems

Some of the interesting things we have shipped in frontend -

• Ability for users to annotate documents so AI can learn which fields to extract.
• Displaying machine learning metrics in simplified ways to end users so they can act based on those metrics
• Letting users build complex visual workflows around our API in our product.
• Let users visualize complex ML metrics in a very simple and intuitive way 

Our Tech Stack

• Databases
• Cassandra DB
• Postgres/MySQL
• Backend
• Golang for API and other microservices
• Python for Machine learning (Tensorflow, Pytorch)
• Frontend
• React, Typescript
• Mobx
• Cloud Providers
• AWS
• GCP for ML heavy workload
• Monitoring/Alerting
• ELK for logging
• Prometheus for Monitoring
• Graphana for dashboards
• Orchestration
• Kubernetes
• DevOps
• Jenkins for CI/CD

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.

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.
• 7+ years of hands-on experience in applied machine learning and data science, with at least 2+ years in a leadership or managerial role.

What you will do:

The role requires you to be part of the team that helps productize the SW stack for our AI compute engine. As part of the software team, you will be responsible for the development, enhancement, and maintenance of software kernels for next-generation AI hardware. You possess experience building software kernels for HW architectures. You possess a very strong understanding of various hardware architectures and how to map algorithms to the architecture. You understand how to map computational graphs generated by AI frameworks to the underlying architecture. You have had past experience working across all aspects of the full stack toolchain and understand the nuances of what it takes to optimize and trade off various aspects of hardware-software co-design. You are able to build and scale software deliverables in a tight development window. You will work with a team of compiler experts to build out the compiler infrastructure, working closely with other software (ML, systems) and hardware (mixed signal, DSP, CPU) experts in the company.

What you will bring:

Minimum:
MS or PhD in Computer Engineering, Math, Physics, or related degree with 10+ years of industry experience Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals Proficient in C/C++ and Python development in Linux environment and using standard development tools Experience implementing algorithms in high-level languages such as C/C++ and Python Experience implementing algorithms for specialized hardware such as FPGAs, DSPs, GPUs, AI accelerators using libraries such as CuDA etc. Experience in implementing operators commonly used in ML workloads—GEMMs, Convolutions, BLAS, SIMD operators for operations like softmax, layer normalization, pooling, etc. Experience with development for embedded SIMD vector processors such as Tensilica. Self-motivated team player with a strong sense of ownership and leadership

Preferred:
Prior startup, small team, or incubation experience.
Experience with ML frameworks such as TensorFlow and/or PyTorch.
Experience working with ML compilers and algorithms, such as MLIR, LLVM, TVM, Glow, etc.
Experience with a deep learning framework (such as PyTorch or TensorFlow) and ML models for CV, NLP, or recommendation.
Work experience at a cloud provider or AI comp.

Location: Hybrid, working onsite at our Bengaluru, India offices 3-5 days per week.

What you will do:

 The role requires you to be part of the team that helps productize the SW stack for our AI compute engine. As part of the software team, you will be responsible for the development,

enhancement, and maintenance of software kernels for next-generation AI hardware. You possess experience building software kernels for HW architectures. You possess a very strong

understanding of various hardware architectures and how to map algorithms to the architecture. You understand how to map computational graphs generated by AI frameworks to the

underlying architecture. You have had past experience working across all aspects of the full stack toolchain and understand the nuances of what it takes to optimize and trade off various

aspects of hardware-software co-design. You can build and scale software deliverables in a tight development window. You will work with a team of compiler experts to build out the

compiler infrastructure, working closely with other software (ML, systems) and hardware (mixed signal, DSP, CPU) experts in the company.

What you will bring: 

Minimum:

MS in computer engineering, math, physics, or a related degree with 5+ years of industry experience or PhD in computer engineering, math, physics, or a related degree with 1+ years of industry experience

Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals.
Proficient in C/C++ and Python development in Linux environments and using standard development tools.
Experience implementing algorithms in high-level languages such as C/C++ and Python.
Experience implementing algorithms for specialized hardware such as FPGAs, DSPs, GPUs, and AI accelerators using libraries such as CUDA, etc. 
Experience in implementing operators commonly used in ML workloads—GEMMs, Convolutions, BLAS, SIMD operators for operations like softmax, layer normalization, pooling, etc.

Experience with development for embedded SIMD vector processors such as Tensilica.
Self-motivated team player with a strong sense of ownership and leadership.

Preferred:

Prior startup, small team, or incubation experience.

Experience with ML frameworks such as TensorFlow and/orPyTorch.

Experience working with ML compilers and algorithms, such as MLIR, LLVM, TVM, Glow, etc.

Experience with a deep learning framework (such as PyTorch or TensorFlow) and ML models for CV, NLP, or recommendation

Work experience at a cloud provider or AI compute/subsystem company.

Lookout, Inc. is a globally recognized cybersecurity leader delivering advanced protection for the most vulnerable element of any enterprise security strategy — human error and manipulation. Cloud-native by design, the Lookout platform offers rapid, scalable deployment and simplified security operations, defending the frontline of human-centric attacks—the mobile device. Attackers now target the human element more than ever, with mobile devices providing the most direct path to their victims. Using social engineering techniques that exploit basic human instincts like trust, curiosity, and urgency, they deceive users into revealing sensitive credentials, allowing them to slip past legacy security solutions.

Lookout Endpoint Detection and Response (EDR) continuously monitors mobile endpoints for signs of human-centric attacks, as well as traditional malware, software vulnerabilities, and other anomalous activity. It uses advanced threat detection techniques, including artificial intelligence (AI) and behavioral analysis, to identify threats before they escalate across the enterprise. Learn more at www.lookout.com and follow us on the Lookout Blog, LinkedIn, and X.

Lookout’s backend system supports a massive volume of data and an increasingly high level of demand, from data ingestion to delivery to dynamic analysis. We’re looking for talented and motivated engineers to build core components and services, as well as to contribute to evolving the architecture. We’re a small team working on a very large, modern system with a user base of millions, so you’ll get to work on a cutting-edge product and service on a large scale. We’re responsible for building and maintaining several of the services powering the various Lookout applications..

What you’ll do:

• You will be part of a dynamic and technically diverse group of engineers, where you will get to contribute, influence, learn and grow top notch technical skill sets, while building key features for our customers.
• Own the full machine learning lifecycle, from initial research and design to production deployment, monitoring, and continuous retraining.
• Establish and implement robust frameworks to train, evaluate, stress-test, and monitor ML/AI systems, driving continuous improvement and preventing model drift.
• Address and navigate real-world scale and performance challenges, ensuring all ML/AI models and systems are efficient, robust, and maintain target quality/latency under production constraints.
• Set technical direction as a senior Individual Contributor (IC) and mentor junior engineers.
• Quality is the forefront of all we do, so you will assist with improving all forms of automated testing (unit, integration, functional etc).
• We believe in, and practice, end to end service ownership, so you will fully participate in the ownership of your services and components, including on-call duties.

What we’re looking for: 

• BS/MS in Computer Science or related field/degree with at least  5-8 years of  work experience.
• A proven track record of architecting and deploying practical, high-impact ML/AI systems over multiple years, translating complex models into robust, real-world solutions.
• Experience working cross-functionally with data engineers, platform engineers, and product stakeholders to bring ML/AI systems to life.
• Expert proficiency in Python and strong software engineering skills, including the ability to write reliable, production-grade code. In-depth experience with major ML/Deep Learning frameworks: PyTorch, TensorFlow, scikit-learn.
• Familiarity with modern AI/ML stacks like Hugging Face and LangChain.
• Deep expertise in a wide range of standard ML algorithms, including classification, clustering, regression, and deep learning models. 
• Hands-on experience with the LLM/RAG stack components: embeddings, knowledge graphs, vector databases, retrieval strategies, and prompt engineering. 
• Proven ability to measure and optimize model efficacy using statistical methods.
• Hands-on experience with production ML infrastructure, including feature stores, model management, training/serving pipelines (MLOps), and monitoring tools. 
• Up-to-date with new advances in NLP, LLMs and agent-frameworks.
• Strong grasp of software engineering fundamentals and algorithms.
• Experience with implementing secure, scalable API services.

Bonus Points:

• Practical experience applying advanced techniques to enhance model efficiency, including model distillation (creating smaller, faster student models) and model quantization (reducing memory footprint and latency).
• Experience with efficient Large Language Model (LLM) fine-tuning methods like LoRA and other PEFT techniques.
• Experience working with coding agents (Cursor, Copilot, Claude Code etc..)
• Experience with event streaming frameworks, technologies, patterns and architectures (particularly Kafka or similar)
• Professional programming experience with Scala and Golang
• Experience with serverless architectures on AWS, GCP.
• Experience with Kubernetes, container technology (Docker, ECS, EKS).

Lookout, Inc. is a globally recognized cybersecurity leader delivering advanced protection for the most vulnerable element of any enterprise security strategy — human error and manipulation. Cloud-native by design, the Lookout platform offers rapid, scalable deployment and simplified security operations, defending the frontline of human-centric attacks—the mobile device. Attackers now target the human element more than ever, with mobile devices providing the most direct path to their victims. Using social engineering techniques that exploit basic human instincts like trust, curiosity, and urgency, they deceive users into revealing sensitive credentials, allowing them to slip past legacy security solutions.

Lookout Endpoint Detection and Response (EDR) continuously monitors mobile endpoints for signs of human-centric attacks, as well as traditional malware, software vulnerabilities, and other anomalous activity. It uses advanced threat detection techniques, including artificial intelligence (AI) and behavioral analysis, to identify threats before they escalate across the enterprise. Learn more at www.lookout.com and follow us on the Lookout Blog, LinkedIn, and X.

Lookout’s backend system supports a massive volume of data and an increasingly high level of demand, from data ingestion to delivery to dynamic analysis. We’re looking for talented and motivated engineers to build core components and services, as well as to contribute to evolving the architecture. We’re a small team working on a very large, modern system with a user base of millions, so you’ll get to work on a cutting-edge product and service on a large scale. We’re responsible for building and maintaining several of the services powering the various Lookout applications..

What you’ll do:

• You will be part of a dynamic and technically diverse group of engineers, where you will get to contribute, influence, learn and grow top notch technical skill sets, while building key features for our customers.
• Own the full machine learning lifecycle, from initial research and design to production deployment, monitoring, and continuous retraining.
• Establish and implement robust frameworks to train, evaluate, stress-test, and monitor ML/AI systems, driving continuous improvement and preventing model drift.
• Address and navigate real-world scale and performance challenges, ensuring all ML/AI models and systems are efficient, robust, and maintain target quality/latency under production constraints.
• Set technical direction as a senior Individual Contributor (IC) and mentor junior engineers.
• Quality is the forefront of all we do, so you will assist with improving all forms of automated testing (unit, integration, functional etc).
• We believe in, and practice, end to end service ownership, so you will fully participate in the ownership of your services and components, including on-call duties.

What we’re looking for: 

• BS/MS in Computer Science or related field/degree with at least  5-8 years of  work experience.
• A proven track record of architecting and deploying practical, high-impact ML/AI systems over multiple years, translating complex models into robust, real-world solutions.
• Experience working cross-functionally with data engineers, platform engineers, and product stakeholders to bring ML/AI systems to life.
• Expert proficiency in Python and strong software engineering skills, including the ability to write reliable, production-grade code. In-depth experience with major ML/Deep Learning frameworks: PyTorch, TensorFlow, scikit-learn.
• Familiarity with modern AI/ML stacks like Hugging Face and LangChain.
• Deep expertise in a wide range of standard ML algorithms, including classification, clustering, regression, and deep learning models. 
• Hands-on experience with the LLM/RAG stack components: embeddings, knowledge graphs, vector databases, retrieval strategies, and prompt engineering. 
• Proven ability to measure and optimize model efficacy using statistical methods.
• Hands-on experience with production ML infrastructure, including feature stores, model management, training/serving pipelines (MLOps), and monitoring tools. 
• Up-to-date with new advances in NLP, LLMs and agent-frameworks.
• Strong grasp of software engineering fundamentals and algorithms.
• Experience with implementing secure, scalable API services.

Bonus Points:

• Practical experience applying advanced techniques to enhance model efficiency, including model distillation (creating smaller, faster student models) and model quantization (reducing memory footprint and latency).
• Experience with efficient Large Language Model (LLM) fine-tuning methods like LoRA and other PEFT techniques.
• Experience working with coding agents (Cursor, Copilot, Claude Code etc..)
• Experience with event streaming frameworks, technologies, patterns and architectures (particularly Kafka or similar)
• Professional programming experience with Scala and Golang
• Experience with serverless architectures on AWS, GCP.
• Experience with Kubernetes, container technology (Docker, ECS, EKS).

In India, we have our teams based in Pune, Mumbai, Delhi and, Bangalore. We pride ourselves on being client-focused and collaborative, on the pioneering edge of technology. We also have fun. Whether it’s office happy hours, team outings, or game nights, we believe in working with people we like to hang out with.

Ideal candidate traits

If you identify as a team player and you are humble, hungry, and smart — we would love to get to know you. We believe these qualities to be vital to building a strong, productive, and collaborative work environment, where everyone is committed to achieving common goals and working towards shared success.

We are looking for people who are willing to learn from others, who can put their egos aside and prioritise the needs of the team. You should also be highly motivated, driven to succeed, and always looking for ways to improve. We value emotional intelligence, excellent communication skills, and a collaborative spirit that enables them to build strong relationships with teammates and work effectively towards shared goals.

At AlphaSense we are committed to fostering a work culture that encourages these qualities and values the contributions of team players who exhibit them. We seek to match the ambition of ideal team players by offering opportunities for personal and professional growth, providing the resources and support necessary to achieve their goals, and creating an environment where hard work, dedication, and teamwork are celebrated and rewarded. At AlphaSense we are building teams of ideal players who embody the core values of Sisu, driving the company’s success and helping us to create a positive impact on the world.

Technologies that we work with:

Frontend

ReactJS, TypeScript, Micro Frontends

Applications

NodeJS, TypeScript, GraphQL, Java 17, Spring Boot, Python, FastAPI

Backend

Java 17, Spring Boot, Python, FastAPI, Kafka

Search and AI

Apache Solr, Elasticsearch, Vector Search, ML, LLM, Pytorch, Tensorflow

Cloud architecture

AWS, GCP, Kubernetes, Crossplane, Argo CD

Quality & reliability

Cypress, Selenium, Selenide, Playwright, Rest Assured, K6, Prometheus, Loki, Grafana

Ready to Make an Impact?

Join our talent community, hear about exciting career opportunities, and get tailored job recommendations based on your interests.

If you’re looking for a challenge, if you love finding things that need interesting solutions, AlphaSense is a great place to come. It is a place for builders, for people who want to create the next thing.

Want to hear more?

Contact us and let’s figure out together if we can find a common path. Tell us about yourself and your background in your own words.

The Role

We’re looking for a seasoned Staff Machine Learning Engineer to shape and scale the backbone of our production ML ecosystem. In this role, you will architect high-performing ML systems that power our geospatial intelligence platform, transforming large-scale satellite and aerial imagery into actionable insights. You’ll lead end-to-end ownership—from model deployment and MLOps to infrastructure design—while partnering closely with data science, platform engineering, and product teams to deliver reliable, scalable, and cost-efficient ML solutions. If you thrive at the intersection of deep technical expertise, system design, and cross-functional collaboration, this role is for you.

How you'll make an impact:

ML System Architecture & Production Deployment

• Design, build, and maintain end-to-end ML pipelines for batch processing of satellite and aerial imagery
• Deploy and scale ML models in production on AWS infrastructure, leveraging services like SageMaker, Bedrock,or custom-built solutions
• Implement MLflow for experiment tracking, model versioning, and model registry management
• Architect batch inference systems optimized for throughput and cost-efficiency
• Work with geospatial data formats and coordinate reference systems
• Collaborate with data scientists to transition models from research to production
• Partner with platform engineering to build scalable compute, GPU clusters, and storage layers

ML Operations & Reliability

• Implement comprehensive model monitoring systems to track performance degradation and data drift
• Design and execute canary deployments and A/B testing frameworks for safe model rollouts
• Build active learning pipelines to continuously improve model performance with minimal labeling effort
• Establish model evaluation frameworks and performance benchmarking processesCreate alerting and observability systems for production ML workloads

Technical Leadership

• Mentor ML engineers and data scientists on best practices for production ML
• Drive technical decision-making on ML infrastructure and tooling
• Collaborate with platform and data engineering teams to optimize the ML stack
• Establish engineering standards and contribute to architectural roadmaps

What we’re looking for:

• 5+ years of experience in machine learning engineering with 2+ years in a senior or lead capacity
• Proven track record deploying and maintaining ML systems in production using AWS services (SageMaker,Lambda, ECS/EKS, S3, etc.)
• Strong hands-on experience with tools like MLflow, WandB, or similar for experiment tracking and model management
• Deep expertise in image segmentation and computer vision techniques using frameworks like PyTorch or TensorFlow
• Production experience with ensemble models (xgboost, lightgbm, RF)

ML Operations Expertise

• Experience implementing model monitoring, drift detection, and alerting systems
• Hands-on experience with canary deployments, A/B testing and Shadow deployments for ML models
• Knowledge of active learning strategies and human-in-the-loop ML systems
• Strong understanding of model evaluation metrics, bias detection, and performance analysis

Technical Skills

• Expert-level Python programming with ML libraries (scikit-learn, PyTorch/TensorFlow, NumPy, pandas, etc)
• Experience with distributed batch processing frameworks (Airflow, Step Functions, Argo Workflows, Spark,Dask, Ray or similar)
• Proficiency with AWS ML ecosystem and infrastructure-as-code (Terraform, CloudFormation)
• Hands-on experience with dataset versioning tools such as DVC, LakeFS, Delta Lake, Quilt, or Pachyderm
• Strong software engineering fundamentals: unit/integration testing, CI/CD, version control, observability, designpatterns
• Experience with containerization (Docker, Kubernetes) for model deployment
• Good to have experience with ML Orchestration tools like Kubeflow, Vertex AI, etc
• Nice to have experience with GPUs: scheduling GPU jobs, optimizing GPU performance, memory profiling

We are proud to be an equal-opportunity employer. We are committed to embracing diversity and inclusion in our hiring practices, and we promote a work environment where everyone, from any race, color, religion, sex, sexual orientation, gender identity, or national origin, can do their best work.

Job Title: GenAI Developer/ Engineer

About Us

“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. 

WHY JOIN CAPCO?

You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.

MAKE AN IMPACT

Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.

#BEYOURSELFATWORK

Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.

CAREER ADVANCEMENT

With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.

DIVERSITY & INCLUSION

We believe that diversity of people and perspective gives us a competitive advantage.

Location - Bangalore

Experience - 6 to 10

Skills and Qualifications:

Preferred skills:

Programming: Advanced Python (async programming, OOP, REST APIs, FastAPI, Flask, Pandas, NumPy)

GenAI Frameworks: LangChain, LlamaIndex, Haystack, Semantic Kernel

Machine Learning and AI: Snowflake Cortex, TensorFlow, PyTorch

Key Responsibilities:

• Develop scalable Python applications focused on GenAI
• Knowledge of Snowflake Cortex is a big plus.
• Learn and apply techniques like document chunking and embeddings
• Proficient in both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, Cassandra) databases, including schema design and optimization.
• Design, develop, and fine-tune applications built around foundation models (e.g., LLMs, multimodal models) for specific business needs
• Implement and experiment with generative AI techniques, including but not limited to Retrieval-Augmented Generation (RAG) and prompt engineering
• Lead the implementation of intelligent autonomous agents and multi-agent systems capable of complex decision-making, task execution, and interaction with external systems
• Utilize and contribute to agentic AI frameworks (e.g., LangChain, AutoGen, Semantic Kernel, Crew AI) to build robust and scalable AI agents
• Develop and integrate Model Context Protocol (MCP) solutions to standardize how AI applications access and utilize external data sources, tools, and real-time information
• Lead the development of full-stack applications that integrate generative AI models and agentic systems, ensuring seamless user experiences
• Work with front-end technologies (e.g., React, Angular, Vue.js, JavaScript, TypeScript, HTML, CSS) and back-end frameworks (e.g., Python with Flask/Django/FastAPI, Node.js, Go)
• Design and implement scalable RESTful APIs and microservices to expose AI functionalities
• Deploy, manage, and optimize AI/ML workloads and full-stack applications on at least one major cloud platform (AWS, Azure, or GCP)
• Implement LLMOps/MLOps and DevOps best practices for continuous integration, continuous delivery (CI/CD), model deployment, monitoring, and lifecycle management
• Follow coding best practices and contribute to testing and documentation
• Stay abreast of the latest advancements in generative AI, agentic systems, foundation models, and related fields through continuous research and experimentation
• Collaborate effectively with cross-functional teams, including product managers, data scientists, researchers, and other engineers
• Communicate effectively with both technical and non-technical team members, ensuring alignment and understanding across all project phases.

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.

Staff Data Scientist – Supply Chain AI (Small Language Models)  

At Avathon, we build AI products that solve real industrial problems at scale. We believe the future of enterprise AI lies in small, focused, high-performance models—deeply grounded in domain context—not just large, generic systems. 

We’re looking for an experienced Data Scientist to join our Supply Chain AI team in India. In this role, you’ll design, fine-tune, and deploy optimized Small Language Models (SLMs) that power production-grade AI features across logistics, planning, inventory, and demand forecasting. 

What Makes This Role Unique 

This is a product-first data science role. You won’t just build models—you’ll own how they show up in real products used by large enterprises. Your work becomes the intelligence layer that sits on top of our graph and indexing systems and directly drives customer outcomes. 

What You’ll Do 

• Build and fine-tune SLMs/LLMs for production use cases such as semantic search, forecasting, contract intelligence, and conversational insights. Optimize models for performance, cost, and latency using PEFT, quantization, and efficient inference techniques 

• Embed supply chain knowledge into models by working closely with domain experts and product teams 

• Enable agentic workflows, allowing AI Assistants to execute planning, optimization, and decision-support tasks 

• Integrate models into products using custom Lambdas, and a Graph-based microservices architecture  

• Apply vector search and semantic reasoning to help customers navigate complex supply chain relationships 

• Work with real enterprise data—ERP, logistics, inventory, supplier, and contract datasets 

• Deploy and operate models using strong MLOps practices on platforms like AWS, GCP or AZURE 

• Measure and improve quality, reducing hallucinations and improving reliability through continuous evaluation 
• Partner with engineering, product, and operations teams to ship impactful AI features end-to-end 

What We’re Looking For 

• Experience working with SLMs (Mistral, Phi, Nemotron, Llama variants), applying parameter-efficient fine-tuning (LoRA/QLoRA) to optimize task-specific natural language query answering with high accuracy and minimized hallucinations. 

• Strong understanding of supply chain data and workflows (logistics, inventory, procurement, ERP systems) 

• Familiarity with Knowledge Graphs and graph-based data modeling, including designing and querying Neo4j graphs for relationship-driven insights. 

• Solid hands-on skills in Python, PyTorch/TensorFlow, GraphQL, and vector databases 

• 8+ years of experience in forecasting, optimization, supply chain analytics, or AI-driven products 

• Experience designing Retrieval-Augmented Generation pipelines using document chunking, metadata filtering, hybrid (dense + sparse) retrieval, and SLM/LLM grounding for enterprise knowledge search. 

• Hands-on experience building and tuning FAISS-based vector indexes (IVF, HNSW, PQ) for large-scale semantic similarity search with low-latency production deployment 

• Experience taking models from prototype to production 

• Bonus: reinforcement learning, MARL, graph neural networks, or probabilistic modeling 

• Clear communication skills and a strong sense of product ownership 

Why Avathon 

You’ll work on core AI products, not experiments—solving complex supply chain problems for global enterprises, while building from India as a key innovation hub. 

If you enjoy shipping AI that delivers measurable business value, this role is for you.