About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and
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Ai Ml Dev in Bengaluru
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Senior Data Scientist (FullStack Machine Learning) About Team Myntra Data Science team delivers a large number of data science solutions for the company which are deployed at various customer touch points every quarter. The models create significant revenue and customer experience impact. The models involve real-time, near-real-time and offline solutions with varying latency requirements. The models are built using massive datasets. You will have the opportunity to be part of a rapidly growing organization and gain exposure to all the parts of a comprehensive ecommerce platform. You’ll also get to learn the intricacies of building models that serve millions of requests per second at sub second latency. The team takes pride in deploying solutions that not only leverage state of the art machine learning models like graph neural networks, diffusion models, transformers, representation learning, optimization methods and bayesian modeling but also contribute to research literature with multiple peer-reviewed research papers. Roles and Responsibilities Design, develop and deploy machine learning models and algorithms to solve complex business problems for Myntra Recsys, Search, Vision, SCM, Pricing, Forecasting, Trend and Virality prediction, Gen AI and other areas. Theoretical understanding and practice of machine learning and expertise in one or more of the topics, such as, NLP, Computer Vision, recommender systems and Optimisation. Implement robust and reliable software solutions for model deployment. Set up and maintain CI/CD pipelines for automated testing and deployment. Maintain machine learning pipelines, contributing to tasks like data cleaning, feature extraction and basic model training. Collaborate with Platforms and Engineering to make sure the ML models built are deployed and integrated into the systems. Working with the Data Platforms teams for understanding and collecting the data. Write clean, maintainable and efficient code. Conduct performan
Senior Data Scientist (FullStack Machine Learning) About Team Myntra Data Science team delivers a large number of data science solutions for the company which are deployed at various customer touch points every quarter. The models create significant revenue and customer experience impact. The models involve real-time, near-real-time and offline solutions with varying latency requirements. The models are built using massive datasets. You will have the opportunity to be part of a rapidly growing organization and gain exposure to all the parts of a comprehensive ecommerce platform. You’ll also get to learn the intricacies of building models that serve millions of requests per second at sub second latency. The team takes pride in deploying solutions that not only leverage state of the art machine learning models like graph neural networks, diffusion models, transformers, representation learning, optimization methods and bayesian modeling but also contribute to research literature with multiple peer-reviewed research papers. Roles and Responsibilities Design, develop and deploy machine learning models and algorithms to solve complex business problems for Myntra Recsys, Search, Vision, SCM, Pricing, Forecasting, Trend and Virality prediction, Gen AI and other areas. Theoretical understanding and practice of machine learning and expertise in one or more of the topics, such as, NLP, Computer Vision, recommender systems and Optimisation. Implement robust and reliable software solutions for model deployment. Set up and maintain CI/CD pipelines for automated testing and deployment. Maintain machine learning pipelines, contributing to tasks like data cleaning, feature extraction and basic model training. Collaborate with Platforms and Engineering to make sure the ML models built are deployed and integrated into the systems. Working with the Data Platforms teams for understanding and collecting the data. Write clean, maintainable and efficient code. Conduct performan
Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire. Offices: New York | Dallas | San Francisco | Lima | Bengaluru The below role is for our Bengaluru office. About the Role: We are looking for Associate Manager Analytics who will work on a broad range of data analytics, data visualization and business intelligence problems across a variety of industries. More specifically, you will: • Engage with clients to understand their business context • Understand business processes and map the complete process in visual formats. • Translate business problems into analytical structures and solve using statistical/ML techniques • Manage a team of data analysts to deliver solutions for clients. • Collaborate with a team of data scientists and engineers to embed AI and analytics into the business decision processes. Desired Skills & Competencies: • Developing and enhancing algorithms and models to solve business problem. • Providing end-to-end analysis support across different industry domains and application areas. • Generate data cuts/outputs according to agreed specifications (for example, survey data clean up, weighting data, recoding variables, creating custom tabular views, and running cross-tabulations) • Conducting quantitative analyses and interpreting results • Proficient in visualisation tools such as Power BI, Tableau, QlikView, Spotfire (Any). • Proficient in MS SQL Data
Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire. Offices : New York | Dallas | San Francisco | Lima | Bengaluru The below role is for our Bengaluru office. About the Role : You will work on a broad range of cutting-edge data science and machine learning problems across a variety of industries. You will be engaging with clients to understand their business context. If you are passionate to work on complex unstructured business problems that can be solved using data science and machine learning, we would like to talk to you. Role: ALDS Mandate Skills & Competencies: Experience in Programming (Python, R, SQL, NoSQL, Spark) with ML tools & Cloud Technology (AWS, Azure, GCP) Experience in Python libraries such as NumPy, pandas, scikit-learn, tensor-flow, scapy, scrapy, BERT etc. Good understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making. Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, PCA etc.) Engaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc. Contribute to internal product development initiatives related to data science. Develop data science roadmap, and guide data scientist to meet their deliverables. Handling end-to-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and c
Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Everpure is moving from an application-centric world to a data-centric one — where AI depends on trusted, well-governed, and contextualized data across the business. As part of this shift, we're looking for a Staff Analyst, AI & Automation to lead the technical build of AI and applied ML capability inside the analytics function. This is an individual contributor role — you will not manage people. Your leverage comes from what you build and ship: AI agents, applied ML models, and automated analytics workflows that change how insight gets produced, working closely with cross-functional teams to bring these to life. AI is changing by the week, not by the year. We're not looking for someone who adopts AI once it's already mainstream — we want someone who is naturally ahead of the curve: scanning what's new, testing it quickly, and bringing it into the team before it's obvious to everyone else. This role has real freedom to experiment, rethink existing approaches, and change course as the field moves. WHAT YOU'LL DO Own the technical build of AI-powered analytics tools — including RAG pipelines, LLM-assisted querying, agent workflows, and applied ML models. Our current stack includes Glean, Gemini, Claude Code and Snowflake Cortex, and we expect that to change; we care more that you pick up new tools quickly than that you already know ours. Apply data science methods (forecasting, segmentation, anomaly detection, c
About AiDASH AiDASH is leading the PreventionFirst™movement for electric utilities and transforming grid resilience through its pioneering platform that unifies vegetation, asset, storm, and wildfire intelligence. Powered by SatelliteFirst™ Inspection & Monitoring, AiDASH delivers comprehensive visibility across the entire grid at the right frequency and budget, using the right data modality. More than 200 customers trust AiDASH to keep the lights on, spend where it counts, and defend every decision, Securing Tomorrow across every mile of the grid. Learn more at www.aidash.com. The PreventionFirst movement is growing, and so is the recognition behind it. In 2026, Forbes named AiDASH one of America's Best Startup Employers for the 4th consecutive year, and TIME included AiDASH among America's Top GreenTech Companies for the 3rd year in a row. Deloitte Technology Fast 500 ™ ranked AiDASH No. 12 in the San Francisco Bay Area, and No. 59 overall in their selection of the top 500 for 2024. Join us in Securing Tomorrow Together! The Role AiDASH is looking for a high-agency Program Manager to help scale our AI Data Ops function: the team responsible for sourcing, processing, and annotating the satellite and remote sensing imagery that powers our AI/ML models. This role is a new addition to the leadership team, created specifically to bring an automation-first, numbers-backed, process-driven operating model to how Ops runs . This role is designed to reduce operational complexity over time, not to manage individual queues or projects indefinitely. You will sit at the intersection of strategy, operations, vendor management, and data science delivery, helping AI Data Ops evolve from a fast-scaling function into a well-designed, repeatable operating system. You will need to zoom in to solve real problems on the ground — a stuck vendor SLA, a high priority escalation, a broken handoff — and z
About AiDASH AiDASH is leading the PreventionFirst™movement for electric utilities and transforming grid resilience through its pioneering platform that unifies vegetation, asset, storm, and wildfire intelligence. Powered by SatelliteFirst™ Inspection & Monitoring, AiDASH delivers comprehensive visibility across the entire grid at the right frequency and budget, using the right data modality. More than 200 customers trust AiDASH to keep the lights on, spend where it counts, and defend every decision, Securing Tomorrow across every mile of the grid. Learn more at www.aidash.com. The PreventionFirst movement is growing, and so is the recognition behind it. In 2026, Forbes named AiDASH one of America's Best Startup Employers for the 4th consecutive year, and TIME included AiDASH among America's Top GreenTech Companies for the 3rd year in a row. Deloitte Technology Fast 500 ™ ranked AiDASH No. 12 in the San Francisco Bay Area, and No. 59 overall in their selection of the top 500 for 2024. Join us in Securing Tomorrow Together! The Role As a Geospatial Analyst at AiDASH, you will produce high-quality annotated datasets from diverse imagery sources — satellite, LiDAR, aerial, and ground-based panoramic images and videos. Your work will directly feed AI/ML pipelines and client deliverables that protect critical infrastructure. This role demands a sharp eye for detail, comfort working with visual and geospatial data at scale, and fluency with modern AI tools. You won’t just annotate images; you’ll build AI-accelerated workflows that make the entire team faster. How You’ll Make an Impact Annotate and label imagery (satellite, LiDAR, aerial, drone, ground-based panoramic photos and videos) to identify, classify, and delineate features such as vegetation, assets, terrain, and infrastructure components Prepare,
About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. The Role We are looking for an Engineering Leader to manage and scale multiple product lines in the Voice, BPO, and Workforce Management space. This is a high-impact leadership role that sits at the intersection of real-time voice systems, operations research, and data-intensive platform engineering. You will report directly to the Head of Engineering and own the engineering organization that builds the infrastructure powering Ema’s Voice AI Employees, Agent QA, auto-learning pipelines, rich analytics, and workforce optimization capabilities — all operating as scalable, multi-tenant systems deployed across global geographies. You will collaborate with Product, ML/AI, and Go-to-Market teams to translate customer needs into production systems that handle high volumes of voice data, deliver real-time insights, and continuously improve through automated learning loops. As the owner of multiple product lines, you will balance roadmap priorities across Voice, BPO operations, and WFM (work force management) — ensuring each product evolves cohesively while meeting distinct customer needs. What You Will Do Scalable Multi-Tenant Systems Architect and build multi-tenant systems that serve ent
About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Role Overview & Key Responsibilities This is a high-leverage leadership role that spans architecture, execution, and org-building, and will shape the direction of our AI / ML initiatives at Ema. We are seeking an AI / ML technical leader who can take a vision and build it. As a Principal ML Engineer at Ema, you will be a senior technical leader responsible for shaping the machine learning roadmap, architecting large-scale ML systems, driving innovation, and ensuring our mixture of expert models (LLM + SLM + Custom Model) is accurate and performant at scale. You will collaborate across teams (research, product, infra, data, etc.), mentor senior engineers, and influence strategy and execution at company-wide levels. Responsibilities Lead the technical direction of GenAI and agentic ML systems that power enterprise-grade AI agents — spanning reasoning, retrieval, tool use, and integrations across various SaaS products. Architect, design, and implement scalable production pipelines for model training, fine-tuning, retrieval (RAG), agent orchestration, and evaluation — ensuring robustness, latency efficiency, and continuous learning. Define and own the multi-year ML roadmap for GenA
Who We Are Simpplr is the AI-powered intranet for unifying the digital workplace. It brings people, trusted knowledge, apps, and agents into a coherent digital experience. Powered by a proprietary EX Knowledge Graph, Simpplr synthesizes signals and context across connected systems to deliver personalized information and actions. The platform serves as a digital hub supporting communications, engagement, employee services, and work. With low-code extensibility and enterprise-grade security and governance, Simpplr enables confident operation at scale. More than 1,000 organizations — including AAA, the NHS, Penske, and Moderna — trust Simpplr to keep their workforce informed, aligned, and productive. Learn more at simpplr.com . The Opportunity We're looking for a highly skilled Senior Product Manager – Enterprise Search to join our Product Management team . In this role, you'll own the strategy, definition, and execution of enterprise search across Simpplr — powering both Magnus (our AI assistant) and the Simpplr platform. You'll shape how employees find the right knowledge, content, and answers across the entire enterprise, quickly, accurately, and securely. Search is the connective tissue of the employee experience: it is what makes Magnus's answers trustworthy and what makes the Simpplr platform feel intelligent. You'll be responsible for the end-to-end search experience — from how content is ingested, chunked, and indexed, to how it is retrieved, ranked, and grounded into high-quality, permission-aware answers via retrieval-augmented generation (RAG). You'll work closely with AI engineers, search/ML engineers, data scientists, designers, and cross-functional teams to deliver a search foundation that is fast, relevant, and enterprise-grade. This role requires strong technical fluency in modern search and AI concepts — indexing, chunking, embeddings, vector and hybrid retrieval, ranking, and RAG — along with the product judgment to translate them into measurabl
For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Smartsheet is hiring a Senior Machine Learning Operations Engineer to architect our machine learning production lifecycle. Your mission is to maintain and deploy ML models to a scalable, reliable, and secure production environment. You will design and maintain the infrastructure, automation, and monitoring systems that ensure our AI products are high-performing and cost-effective. You will report to our Director, Analytics Engineering & Data Governance and work from our Bangalore, India office. You Will: Model and Pipeline Automation Automate the deployment and retraining of ML models, from training through to production inference, by building and managing complete CI/CD/CT (Continuous Training) pipelines, adhering to MLOps best practices. Build, fine-tune, or use pre-trained LLMs, deep learning models or traditional machine learning models. Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom-built models. Governance & Compliance Implement model versioning, lineage tracking, and auditing to ensure compliance with security and ethical standards. Performance Monitoring Continuously monitor the health and performance of production machine learning models, proactively identifying and correcting model drift, staleness, and performance degradation. Incorporate user feedback for iterative improvements and manage necessary model retraining cycles. Cross-Functional Collaboration Act as the "glue" between Data Scientists (who build models
At Bolna, we’re building tools that change the way teams leverage Voice AI. We’re looking for a Founding Machine Learning Engineer to own the end-to-end lifecycle of building, evaluating, deploying, and improving models that power millions of production conversations. This is a high-impact, high ownership role where you won’t just work on Bolna’s ML stack—you’ll help build the foundation it scales on. Our team includes IIT alumni with experience at Bain, Atlassian, Uber, Zomato, and LinkedIn, and is backed by leading investors. Responsibilities: Build the data engine - Design pipelines to source and clean conversational voice data across Indian languages, accents, and telephony conditions. Fine-tune models that ship - Fine tune and train models to improve accuracy, speed, and reliability across different use-cases. Define what "good" means - Build evaluation datasets and benchmarks for transcription accuracy, voice naturalness, interruption handling, latency, and end-to-end conversation quality. Set up human-in-the-loop pipelines to capture subjective quality at scale. Ship to production - Work with the engineering team to deploy models into a latency-sensitive, high-volume system. Monitor performance in the wild, debug regressions, and iterate fast. Required Skills: 3+ years of hands-on ML experience with deep practical real-world experience in training models. Strong Python and PyTorch fundamentals with exposure in distributed training, and modern fine-tuning techniques (LoRA, QLoRA, DPO, RLHF, etc.). Training data as a first-class problem. Experience designing data pipelines from collection, cleaning, labeling, deduplication, augmentation and treating data quality as a core engineering discipline. Rigorous about evaluation. You know that "looks good in a demo" is not a benchmark. You build the evals before you trust the model. Speech model experience is a plus with real-time / streaming inference experience where you would have contributed to latency optimization
We're hiring an AI Support Engineer to work directly with the founder and build the systems that power customer support at Bolna. This isn't a traditional support role — you'll use AI to make support scale, and you'll partner closely with the business team on the customer conversations that matter most. What you'll do - Work directly with the founder to design and continuously improve how customer support runs at Bolna - Pull and collate data from Intercom to spot patterns, recurring issues, and gaps in how customers are being helped - Build AI-powered workflows that triage, answer, and resolve customer support queries with less manual effort - Design the systems and processes behind a streamlined, scalable support flow — from triage to escalation to resolution - Step in directly on critical customer support situations alongside the business team when it matters - Turn recurring support themes into feedback for product and engineering What we're looking for - 1–3 years of experience in a support, ops, or technical customer-facing role — ideally somewhere that rewarded building your own tools and process, not just following a playbook - Hands-on comfort with AI tools/workflows (prompting, automations, agent builders) — you don't need to be an ML engineer, but you should be someone who reaches for AI to solve a workflow problem - Experience with Intercom or a similar support/helpdesk tool - Sharp, structured communicator — equally comfortable writing to customers and to the founder - Comfortable with ambiguity — this role is being built as you build it Nice to have - Experience setting up support automations, chatbots, or AI agents in a real product company - Familiarity with SQL or basic scripting to pull/analyze support data - Startup experience, especially in a 0-to-1 function
For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Smartsheet is hiring a Senior Analytics Engineer to lead the way in data-driven decision-making. You will be responsible for the creation and maintenance of a governed, reliable, and scalable analytics system, transforming raw data into usable datasets for DS/ML, analytics, and reporting. A key aspect of this role is leading the architecture and implementation of efficient data transformation systems within Snowflake, fostering data democratization and impacting business outcomes. Working closely with BI analysts and Data scientists, you will ensure data accessibility and drive activation on critical customer-facing platforms. This full-time position reports to the Director of Analytics Engineering and is based in Smartsheet’s corporate offices in Bengaluru, India. You Will: Leading the implementation of efficient and scalable systems that optimize data transformations from our data lake in Snowflake into clean, documented data products. Contribute to the design standards and architectural principle standards, designs and processes. Build and maintain a governed, robust, reliable, and scalable analytics system (DW/DV). Collaborating with BI analysts and data scientists to provide proper data accessibility guidelines. Foster data democratization via activation of data on critical platforms like Smartsheet platform, Amplitude, Thoughtspot , Gainsight. Create and contribute to frameworks that improve data quality and observability to identify and resolve issues faster. Create and implement data testing plans, en
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