We’re hiring an Applied AI Researcher in the deep-tech and AI research industry . We are seeking a highly skilled and motivated professional to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions. Key Responsibilities Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness Research and apply reinforcement learning techniques, including RLHF, DPO, GRPO, and others Explore post-training optimization, fine-tuning, and domain adaptation methods Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities Document and communicate findings through technical reports, presentations, and publications Required Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field 4+ years of experience in applied AI research or equivalent industry R&D experience Strong foundations in optimization, probability, and linear algebra Expertise in Python and frameworks like PyTorch or JAX Experience with RL and post-training methods (e.g., SFT, DPO, RLHF) Proficiency in building and aligning small language models (SLMs), including reasoning-specific models Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node) Experience in designing evaluation metrics and performance analysis methodologies Preferred Experience Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.) Experience applying AI to scientific domains like drug discovery, chip design, or materials science Exposure to multimodal models and VLMs Experience with open-ended systems and emergent behavior in agent-based learning Background in computational science (chemistry, physics, EE, or applied math) Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow Experience with domain adaptation, interpretability, and model optimization for deployment Contributions to open-source AI projects Expertise in building GPU-accelerated pipelines and optimizing inference at scale What We Offer Work on high-impact, frontier research with real-world applications Access to high-performance computing resources A collaborative, intellectually stimulating environment Autonomy to explore novel ideas aligned with our mission Competitive salary, benefits, and opportunities for growth Skills: Research,Design,Multi-agent Systems,Models Show more Show less

This role is for one of our clients Industry: Technology, Information and Media Seniority level: Mid-Senior level Min Experience: 5 years Location: Bengaluru, India, Karnataka JobType: full-time We are seeking a Big Data Engineer with deep technical expertise to join our fast-paced, data-driven team. In this role, you will be responsible for designing and building robust, scalable, and high-performance data pipelines that fuel real-time analytics, business intelligence, and machine learning applications across the organization. If you thrive on working with large datasets, cutting-edge technologies, and solving complex data engineering challenges, this is the opportunity for you. What You’ll Do Design & Build Pipelines : Develop efficient, reliable, and scalable data pipelines that process large volumes of structured and unstructured data using big data tools. Distributed Data Processing : Leverage the Hadoop ecosystem (HDFS, Hive, MapReduce) to manage and transform massive datasets. Starburst (Trino) Integration : Design and optimize federated queries using Starburst, enabling seamless access across diverse data platforms. Databricks Lakehouse Development : Utilize Spark, Delta Lake, and MLflow on the Databricks Lakehouse Platform to enable unified analytics and AI workloads. Data Modeling & Architecture : Work with stakeholders to translate business requirements into flexible, scalable data models and architecture. Performance & Optimization : Monitor, troubleshoot, and fine-tune pipeline performance to ensure efficiency, reliability, and data integrity. Security & Compliance : Implement and enforce best practices for data privacy, security, and compliance with global regulations like GDPR and CCPA. Collaboration : Partner with data scientists, product teams, and business users to deliver impactful data solutions and improve decision-making. What You Bring Must-Have Skills 5+ years of hands-on experience in big data engineering, data platform development, or similar roles. Strong experience with Hadoop , including HDFS, Hive, HBase, and MapReduce. Deep understanding and practical use of Starburst (Trino) or Presto for large-scale querying. Hands-on experience with Databricks Lakehouse Platform , Spark, and Delta Lake. Proficient in SQL and programming languages like Python or Scala . Strong knowledge of data warehousing, ETL/ELT workflows, and schema design. Familiarity with CI/CD tools, version control (Git), and workflow orchestration tools (Airflow or similar). Nice-to-Have Skills Experience with cloud environments such as AWS , Azure , or GCP . Exposure to Docker , Kubernetes , or infrastructure-as-code tools. Understanding of data governance and metadata management platforms. Experience supporting AI/ML initiatives with curated datasets and pipelines.

Role Summary: The AI/ML Platform Engineering Lead is a pivotal leadership role responsible for managing the day-to-day operations and development of the AI/ML platform team. In this role, you will guide the team in designing, building, and maintaining scalable platforms, while collaborating with other engineering and data science teams to ensure successful model deployment and lifecycle management. You can apply directly using the link below: https://jobs.lever.co/welocalize/628f87a7-4edd-4b4f-b440-3b602aa4dadc Key Responsibilities: Lead and manage a team of platform engineers in developing and maintaining robust AI/ML platforms. Define and implement best practices for machine learning infrastructure, ensuring scalability, performance, and security. Collaborate closely with data scientists and DevOps teams to optimize the ML lifecycle from model training to deployment. Establish and enforce standards for platform automation, monitoring, and operational efficiency. Serve as the primary liaison between engineering teams, product teams, and leadership. Mentor and develop junior engineers, providing technical guidance and performance feedback. Stay abreast of the latest advancements in AI/ML infrastructure and integrate new technologies where applicable. Qualifications: Bachelors or Masters degree in Computer Science, Engineering, or a related field. 8+ years of experience in AI/ML platform development and infrastructure. Proven experience in leading engineering teams and driving large-scale projects. Extensive expertise in cloud infrastructure (AWS, GCP, Azure), MLOps tools (e.g., Kubeflow, MLflow), and infrastructure as code (Terraform) Strong programming skills in Python and Node.js , with a proven track record of building scalable and maintainable systems that support AI/ML workflows. Hands-on experience with monitoring and observability tools, such as Datadog, to ensure platform reliability and performance. Strong leadership and communication skills with the ability to influence cross-functional teams. Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.

Position overview: We are seeking a ML Engineer with a strong background in Machine Learning, Natural Language Processing (NLP), Generative AI, and Retrieval-Augmented Generation (RAG). The ideal candidate will possess 1+ years of hands-on experience in developing and deploying advanced data-driven solutions. You will play a key role in our AI-CoE team, contributing to cutting-edge projects that drive innovation and business value. A special focus area for this role would be to build AI enabled products that would result in the creation of monetizable product differentiators for Tata Communications products and services. Detailed job description & Key Responsibilities: Design, develop, and deploy machine learning systems, including Generative AI models and LLMs. Research and implement state-of-the-art ML algorithms and tools. Conduct data preprocessing, feature engineering, and statistical analysis. Train, fine-tune, and optimize machine learning models for performance and accuracy. Collaborate with cross-functional teams, including data scientists, software engineers, and domain experts. Extend existing ML frameworks and libraries to meet project requirements. Stay updated with the latest advancements in machine learning and AI. Skills: Working knowledge of machine learning and deep learning skills. Strong knowledge of programming knowledge Python, SQL and commonly used frameworks & tools PyTorch, Sci-kit, NumPy, Gen AI tools like langchain/llamaIndex Working knowledge of MLOPs principles and implementing projects with Big Data in batch and streaming mode. - must have Experience in handling databases (SQL and NoSQL) Exposure to MLFlow, KubeFlow, Git CI/CD Experience with containerization tools like Docker, and orchestration tools like Kubernetes Excellent problem-solving skills and a proactive attitude. Strong communication and teamwork abilities. Ability to manage multiple projects and meet deadlines Interview will involve coding test

Position overview: We are seeking a ML Engineer with a strong background in Machine Learning, Natural Language Processing (NLP), Generative AI, and Retrieval-Augmented Generation (RAG). The ideal candidate will possess 1+ years of hands-on experience in developing and deploying advanced data-driven solutions. You will play a key role in our AI-CoE team, contributing to cutting-edge projects that drive innovation and business value. A special focus area for this role would be to build AI enabled products that would result in the creation of monetizable product differentiators for Tata Communications products and services. Detailed job description & Key Responsibilities: Design, develop, and deploy machine learning systems, including Generative AI models and LLMs. Research and implement state-of-the-art ML algorithms and tools. Conduct data preprocessing, feature engineering, and statistical analysis. Train, fine-tune, and optimize machine learning models for performance and accuracy. Collaborate with cross-functional teams, including data scientists, software engineers, and domain experts. Extend existing ML frameworks and libraries to meet project requirements. Stay updated with the latest advancements in machine learning and AI. Skills: Working knowledge of machine learning and deep learning skills. Strong knowledge of programming knowledge Python, SQL and commonly used frameworks & tools PyTorch, Sci-kit, NumPy, Gen AI tools like langchain/llamaIndex Working knowledge of MLOPs principles and implementing projects with Big Data in batch and streaming mode. - must have Experience in handling databases (SQL and NoSQL) Exposure to MLFlow, KubeFlow, Git CI/CD Experience with containerization tools like Docker, and orchestration tools like Kubernetes Excellent problem-solving skills and a proactive attitude. Strong communication and teamwork abilities. Ability to manage multiple projects and meet deadlines Interview will involve coding test

Position overview: We are seeking a Data Scientist with a strong background in Machine Learning, Natural Language Processing (NLP), Generative AI, and Retrieval-Augmented Generation (RAG). The ideal candidate will possess 1+ years of hands-on experience in developing and deploying advanced data-driven solutions. You will play a key role in our AI-CoE team, contributing to cutting-edge projects that drive innovation and business value. A special focus area for this role would be to build AI enabled products that would result in the creation of monetizable product differentiators. Detailed job description & Key Responsibilities: Develop, Test, and Deploy machine learning models for various business and Telco use cases. Perform data preprocessing, feature engineering and ML/DL model evaluation. Optimize and fine-tune models for performance and scalability. Good understanding of NLP concepts and projects involving entity recognition, text classification, and language modelling like GPT/Llama/Claude/Grok Build and refine RAG models to improve information retrieval and answer generation systems. Integrate RAG methods into existing applications to enhance data accessibility and user experience. Work closely with cross-functional teams including software engineers, product managers, and domain experts. Communicate technical concepts to non-technical stakeholders effectively. Document processes, methodologies, and model development for internal and external stakeholders. Skills: Strong knowledge of probability and statistics. Working knowledge of machine learning and deep learning skills. Strong knowledge of programming knowledge Python, SQL and commonly used frameworks & tools PyTorch, Sci-kit, NumPy, Gen AI tools like langchain/llamaIndex Working knowledge of MLOPs principles and implementing projects with Big Data in batch and streaming mode. Excellent problem-solving skills and a proactive attitude. Strong communication and teamwork abilities. Ability to manage multiple projects and meet deadlines Interview will involve coding tests.

Position overview: We are seeking a Data Scientist with a strong background in Machine Learning, Natural Language Processing (NLP), Generative AI, and Retrieval-Augmented Generation (RAG). The ideal candidate will possess 1+ years of hands-on experience in developing and deploying advanced data-driven solutions. You will play a key role in our AI-CoE team, contributing to cutting-edge projects that drive innovation and business value. A special focus area for this role would be to build AI enabled products that would result in the creation of monetizable product differentiators. Detailed job description & Key Responsibilities: Develop, Test, and Deploy machine learning models for various business and Telco use cases. Perform data preprocessing, feature engineering and ML/DL model evaluation. Optimize and fine-tune models for performance and scalability. Good understanding of NLP concepts and projects involving entity recognition, text classification, and language modelling like GPT/Llama/Claude/Grok Build and refine RAG models to improve information retrieval and answer generation systems. Integrate RAG methods into existing applications to enhance data accessibility and user experience. Work closely with cross-functional teams including software engineers, product managers, and domain experts. Communicate technical concepts to non-technical stakeholders effectively. Document processes, methodologies, and model development for internal and external stakeholders. Skills: Strong knowledge of probability and statistics. Working knowledge of machine learning and deep learning skills. Strong knowledge of programming knowledge Python, SQL and commonly used frameworks & tools PyTorch, Sci-kit, NumPy, Gen AI tools like langchain/llamaIndex Working knowledge of MLOPs principles and implementing projects with Big Data in batch and streaming mode. Excellent problem-solving skills and a proactive attitude. Strong communication and teamwork abilities. Ability to manage multiple projects and meet deadlines Interview will involve coding tests.

Job Description: Machine Learning / Data Science Engineer/Data Scientists Location: Pune Experience Required: 3–6 years Type: Full-Time Education: BTech / MTech / MSc / PhD in Computer Science, Data Science, Applied Mathematics, Statistics, or a related field. About Anervea.ai Anervea.ai is building a next-generation intelligence stack for the pharmaceutical industry. Our products help commercial, clinical, and medical affairs teams make smarter decisions—faster. From predicting the success of clinical trials and decoding competitor movement, to surfacing real-time KOL signals and automating HCP engagement, our platform powers strategic decision-making at scale. We’re not a services firm—we’re a product-first, AI-native company solving real problems using applied machine learning, generative AI, and life sciences data. Our clients include major US and EU pharma companies, and our team is a mix of engineers, researchers, and life science domain experts. We’re looking for ML engineers and data scientists who are passionate about learning, driven to build usable solutions , and ready to push boundaries. Role Overview As an ML / Data Science Engineer at Anervea, you’ll work on designing, training, deploying, and maintaining machine learning models across multiple products. You’ll build models that predict clinical trial outcomes, extract insights from structured and unstructured healthcare data, and support real-time scoring for sales or market access use cases. You’ll collaborate closely with AI engineers, backend developers, and product owners to translate data into product features that are explainable, reliable, and impactful. Key Responsibilities Develop and optimize predictive models using algorithms such as XGBoost, Random Forest, Logistic Regression, and ensemble methods Engineer features from real-world healthcare data (clinical trials, treatment adoption, medical events, digital behavior) Analyze datasets from sources like ClinicalTrials.gov, PubMed, Komodo, Apollo.io, and internal survey pipelines Build end-to-end ML pipelines for inference and batch scoring Collaborate with AI engineers to integrate LLM-generated features with traditional models Ensure explainability and robustness of models using SHAP, LIME, or custom logic Validate models against real-world outcomes and client feedback Prepare clean, structured datasets using SQL and Pandas Communicate insights clearly to product, business, and domain teams Document all processes, assumptions, and model outputs thoroughly Technical Skills Required Strong programming skills in Python (NumPy, Pandas, scikit-learn, XGBoost, LightGBM) Experience with statistical modeling and classification algorithms Solid understanding of feature engineering , model evaluation, and validation techniques Exposure to real-world healthcare, trial, or patient data (strong bonus) Comfortable working with unstructured data and data cleaning techniques Knowledge of SQL and NoSQL databases Familiarity with ML lifecycle tools (MLflow, Airflow, or similar) Bonus: experience working alongside LLMs or incorporating generative features into ML Bonus: knowledge of NLP preprocessing, embeddings, or vector similarity methods Personal Attributes Strong analytical and problem-solving mindset Ability to convert abstract questions into measurable models Attention to detail and high standards for model quality Willingness to learn life sciences concepts relevant to each use case Clear communicator who can simplify complexity for product and business teams Independent learner who actively follows new trends in ML and data science Reliable, accountable, and driven by outcomes—not just code Bonus Qualities Experience building models for healthcare, pharma, or biotech Published work or open-source contributions in data science Strong business intuition on how to turn models into product decisions Show more Show less

About Agoda Agoda is an online travel booking platform for accommodations, flights, and more. We build and deploy cutting-edge technology that connects travelers with a global network of 4.7M hotels and holiday properties worldwide, plus flights, activities, and more . Based in Asia and part of Booking Holdings, our 7,100+ employees representing 95+ nationalities in 27 markets foster a work environment rich in diversity, creativity, and collaboration. We innovate through a culture of experimentation and ownership, enhancing the ability for our customers to experience the world. Our Purpose – Bridging the World Through Travel We believe travel allows people to enjoy, learn and experience more of the amazing world we live in. It brings individuals and cultures closer together, fostering empathy, understanding and happiness. We are a skillful, driven and diverse team from across the globe, united by a passion to make an impact. Harnessing our innovative technologies and strong partnerships, we aim to make travel easy and rewarding for everyone. LLM Platform at Agoda Agoda’s LLMOps Platform is at the forefront of enabling scalable, secure, and efficient deployment of Large Language Models (LLMs) and generative AI solutions. Built on robust cloud and on-premises infrastructure, our platform empowers teams to experiment, deploy, and monitor LLM-powered applications with confidence and agility. Our LLMOps team bridges the gap between advanced AI research and real-world production systems, ensuring that LLMs are delivered reliably, responsibly, and at scale. We focus on best practices in model lifecycle management, data privacy, prompt engineering, and continuous improvement to help our users unlock the full potential of generative AI. In This Role, You’ll Get to: Lead the design, development, and implementation of LLMOps solutions for deploying, monitoring, and managing large language models and generative AI systems Collaborate with data scientists, ML engineers, and product teams to build scalable pipelines for LLM fine-tuning, evaluation, and inference Develop and maintain tools for prompt management, versioning, and automated evaluation of LLM outputs Ensure responsible AI practices by integrating data anonymization, bias detection, and compliance monitoring into LLM workflows Develop and maintain monitoring and management tools to ensure the reliability and performance of our on-premises and cloud machine learning platform Work with stakeholders across the organization to understand their generative AI needs and deliver LLMOps solutions that drive business impact Stay up-to-date with the latest trends and technologies in LLMOps, generative AI, and responsible AI, and share your knowledge to keep the team at the cutting edge Mentor junior team members and help them grow their skills and expertise in LLMOps Troubleshoot and resolve issues related to LLM deployment, scaling, and performance What You’ll Need to Succeed: 5+ years of experience in LLMOps, MLOps, Software Engineering, or a related field Strong programming skills in a modern language (Python, Kotlin, Scala, Java, etc.) Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams Commitment to code quality, simplicity, and performance It’s Great if you have: Experience with LLMOps platforms and tools (e.g., Hugging Face, LangChain, Ray, MLFlow, Kubeflow) Familiarity with prompt engineering, retrieval-augmented generation (RAG), and LLM evaluation frameworks Experience with data privacy, PII anonymization, and responsible AI practices Strong knowledge of containerization and orchestration (Docker, Kubernetes) Experience with DevOps, CI/CD, and scalable API development for LLM serving Passion for the engineering challenges of generative AI and scaling LLM solutions Experience designing and building LLMOps infrastructure, including data pipelines, model management, and monitoring tools Deep understanding of LLM architectures (e.g., GPT, Llama) and experience with model fine-tuning, evaluation, and deployment Benefits Flexible hybrid work arrangement with the option to work remotely for part of the year Generous annual leave, sick leave, and public holidays Exclusive accommodation discounts for personal travel Annual allowance for wellness, learning, fitness, and travel experiences Opportunities for career growth through training, certifications, and internal promotions Competitive compensation and comprehensive health benefits Relocation Package (for employee and family): Full visa sponsorship for employees, spouse, and children Support for airfare, travel insurance, and temporary accommodation upon arrival Assistance with moving household goods and pet relocation #newdelhi #Pune #Hyderabad #Bangalore #Mumbai #Bengaluru #Chennai #Kolkata #Lucknow #sanfrancisco #sanjose #losangeles #sandiego #oakland #denver #miami #orlando #atlanta #chicago #boston #detroit #newyork #portland #philadelphia #dallas #houston #austin #seattle #sydney #melbourne #perth #toronto #vancouver #montreal #shanghai #beijing #shenzhen #prague #Brno #Ostrava #cairo #alexandria #giza #estonia #paris #berlin #munich #hamburg #stuttgart #cologne #frankfurt #hongkong #budapest #jakarta #bali #dublin #telaviv #milan #rome #tokyo #osaka #kualalumpur #amsterdam #oslo #manila #warsaw #krakow #bucharest #moscow #saintpetersburg #capetown #johannesburg #seoul #barcelona #madrid #stockholm #zurich #taipei #bangkok #Phuket #istanbul #london #manchester #edinburgh #kiev #hcmc #hanoi #wroclaw #poznan #katowice #rio #salvador #IT #4 #5 Equal Opportunity Employer At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person’s merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics. We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy . Disclaimer We do not accept any terms or conditions, nor do we recognize any agency’s representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee. Show more Show less

Company Description NielsenIQ is a consumer intelligence company that delivers the Full View™, the world’s most complete and clear understanding of consumer buying behavior that reveals new pathways to growth. Since 1923, NIQ has moved measurement forward for industries and economies across the globe. We are putting the brightest and most dedicated minds together to accelerate progress. Our diversity brings out the best in each other so we can leave a lasting legacy on the work that we do and the people that we do it with. NielsenIQ offers a range of products and services that leverage Machine Learning and Artificial Intelligence to provide insights into consumer behavior and market trends. This position opens the opportunity to apply the latest state of the art in AI/ML and data science to global and key strategic projects Job Description We are looking for a Senior Research Scientist with a data-centric mindset to join our applied research and innovation team. The ideal candidate will have a strong background in machine learning, deep learning, operationalization of AI/ML and process automation. You will be responsible for analyzing data, researching the most appropriate techniques, and the development, testing, support and delivery of proof of concepts to resolve real-world and large-scale challenging problems. Job Responsibilities Develop and apply machine learning innovations with minimal technical supervision. Understand the requirements from stakeholders and be able to communicate results and conclusions in a way that is accurate, clear and winsome. Perform feasibility studies and analyse data to determine the most appropriate solution. Work on many different data challenges, always ensuring a combination of simplicity, scalability, reproducibility and maintainability within the ML solutions and source code. Both data and software must be developed and maintained with high-quality standards and minimal defects. Collaborate with other technical fellows on the integration and deployment of ML solutions. To work as a member of a team, encouraging team building, motivation and cultivating effective team relations. Qualifications Essential Requirements Bachelor's degree in Computer Science or an equivalent numerate discipline Demonstrated senior experience in Machine Learning, Deep Learning & other AI fields Experience working with large datasets, production-grade code & operationalization of ML solutions EDA analysis & practical hands-on experience with datasets, ML models (Pytorch or Tensorflow) & evaluations Able to understand scientific papers & develop the idea into executable code Analytical mindset, problem solving & logical thinking capabilities Proactive attitude, constructive, intellectual curiosity & persistence to find answers to questions A high level of interpersonal & communication skills in English & strong ability to meet deadlines Python, Pytorch, Git, pandas, dask, polars, sklearn, huggingface, docker, databricks Desired Skills Masters degree &/or specialization courses in AI/ML. PhD in science is an added value Experience in MLOPs (MLFlow, Prefect) & deployment of AI/ML solutions to the cloud (Azure preferred) Understanding & practice of LLMs & Generative AI (prompt engineering, RAG) Experience with Robotic Process Automation, Time Series Forecasting & Predictive modeling A practical grasp of databases (SQL, ElasticSearch, Pinecone, Faiss) Previous experience in retail, consumer, ecommerce, business, FMCG products (NielsenIQ portfolio) Additional Information With @NielsenIQ, we’re now an even more diverse team of 40,000 people – each with their own stories Our increasingly diverse workforce empowers us to better reflect the diversity of the markets we measure. Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) About NIQ NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook Our commitment to Diversity, Equity, and Inclusion NIQ is committed to reflecting the diversity of the clients, communities, and markets we measure within our own workforce. We exist to count everyone and are on a mission to systematically embed inclusion and diversity into all aspects of our workforce, measurement, and products. We enthusiastically invite candidates who share that mission to join us. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. Our global non-discrimination policy covers these protected classes in every market in which we do business worldwide. Learn more about how we are driving diversity and inclusion in everything we do by visiting the NIQ News Center: https://nielseniq.com/global/en/news-center/diversity-inclusion Show more Show less

About Agoda Agoda is an online travel booking platform for accommodations, flights, and more. We build and deploy cutting-edge technology that connects travelers with a global network of 4.7M hotels and holiday properties worldwide, plus flights, activities, and more . Based in Asia and part of Booking Holdings, our 7,100+ employees representing 95+ nationalities in 27 markets foster a work environment rich in diversity, creativity, and collaboration. We innovate through a culture of experimentation and ownership, enhancing the ability for our customers to experience the world. Our Purpose – Bridging the World Through Travel We believe travel allows people to enjoy, learn and experience more of the amazing world we live in. It brings individuals and cultures closer together, fostering empathy, understanding and happiness. We are a skillful, driven and diverse team from across the globe, united by a passion to make an impact. Harnessing our innovative technologies and strong partnerships, we aim to make travel easy and rewarding for everyone. LLM Platform at Agoda Agoda’s LLMOps Platform is at the forefront of enabling scalable, secure, and efficient deployment of Large Language Models (LLMs) and generative AI solutions. Built on robust cloud and on-premises infrastructure, our platform empowers teams to experiment, deploy, and monitor LLM-powered applications with confidence and agility. Our LLMOps team bridges the gap between advanced AI research and real-world production systems, ensuring that LLMs are delivered reliably, responsibly, and at scale. We focus on best practices in model lifecycle management, data privacy, prompt engineering, and continuous improvement to help our users unlock the full potential of generative AI. In This Role, You’ll Get to: Lead the design, development, and implementation of LLMOps solutions for deploying, monitoring, and managing large language models and generative AI systems Collaborate with data scientists, ML engineers, and product teams to build scalable pipelines for LLM fine-tuning, evaluation, and inference Develop and maintain tools for prompt management, versioning, and automated evaluation of LLM outputs Ensure responsible AI practices by integrating data anonymization, bias detection, and compliance monitoring into LLM workflows Develop and maintain monitoring and management tools to ensure the reliability and performance of our on-premises and cloud machine learning platform Work with stakeholders across the organization to understand their generative AI needs and deliver LLMOps solutions that drive business impact Stay up-to-date with the latest trends and technologies in LLMOps, generative AI, and responsible AI, and share your knowledge to keep the team at the cutting edge Mentor junior team members and help them grow their skills and expertise in LLMOps Troubleshoot and resolve issues related to LLM deployment, scaling, and performance What You’ll Need to Succeed: 5+ years of experience in LLMOps, MLOps, Software Engineering, or a related field Strong programming skills in a modern language (Python, Kotlin, Scala, Java, etc.) Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams Commitment to code quality, simplicity, and performance It’s Great if you have: Experience with LLMOps platforms and tools (e.g., Hugging Face, LangChain, Ray, MLFlow, Kubeflow) Familiarity with prompt engineering, retrieval-augmented generation (RAG), and LLM evaluation frameworks Experience with data privacy, PII anonymization, and responsible AI practices Strong knowledge of containerization and orchestration (Docker, Kubernetes) Experience with DevOps, CI/CD, and scalable API development for LLM serving Passion for the engineering challenges of generative AI and scaling LLM solutions Experience designing and building LLMOps infrastructure, including data pipelines, model management, and monitoring tools Deep understanding of LLM architectures (e.g., GPT, Llama) and experience with model fine-tuning, evaluation, and deployment Benefits Flexible hybrid work arrangement with the option to work remotely for part of the year Generous annual leave, sick leave, and public holidays Exclusive accommodation discounts for personal travel Annual allowance for wellness, learning, fitness, and travel experiences Opportunities for career growth through training, certifications, and internal promotions Competitive compensation and comprehensive health benefits Relocation Package (for employee and family): Full visa sponsorship for employees, spouse, and children Support for airfare, travel insurance, and temporary accommodation upon arrival Assistance with moving household goods and pet relocation #newdelhi #Pune #Hyderabad #Bangalore #Mumbai #Bengaluru #Chennai #Kolkata #Lucknow #sanfrancisco #sanjose #losangeles #sandiego #oakland #denver #miami #orlando #atlanta #chicago #boston #detroit #newyork #portland #philadelphia #dallas #houston #austin #seattle #sydney #melbourne #perth #toronto #vancouver #montreal #shanghai #beijing #shenzhen #prague #Brno #Ostrava #cairo #alexandria #giza #estonia #paris #berlin #munich #hamburg #stuttgart #cologne #frankfurt #hongkong #budapest #jakarta #bali #dublin #telaviv #milan #rome #tokyo #osaka #kualalumpur #amsterdam #oslo #manila #warsaw #krakow #bucharest #moscow #saintpetersburg #capetown #johannesburg #seoul #barcelona #madrid #stockholm #zurich #taipei #bangkok #Phuket #istanbul #london #manchester #edinburgh #kiev #hcmc #hanoi #wroclaw #poznan #katowice #rio #salvador #IT #4 #5 Equal Opportunity Employer At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person’s merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics. We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy . Disclaimer We do not accept any terms or conditions, nor do we recognize any agency’s representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee. Show more Show less

The proliferation of machine log data has the potential to give organizations unprecedented real-time visibility into their infrastructure and operations. With this opportunity comes tremendous technical challenges around ingesting, managing, and understanding high-volume streams of heterogeneous data. As a Machine Learning Engineer at Sumo Logic, you will actively contribute in the design and development of innovative ML-powered product capabilities to help our customers make sense of their huge amounts of log data. This involves working through the entire feature lifecycle including ideation, dataset construction, experimental validation, prototyping, production implementation, deployment, and operations. Responsibilities Identifying and validating opportunities for the application of ML or data-driven techniques Assessing requirements and approaches for large-scale data and ML platform components Driving technical delivery through the full feature lifecycle, from idea to production and operations Helping the team design and implement extremely high-volume, fault-tolerant, scalable backend systems that process and manage petabytes of customer data. Collaborating within and beyond the team to identify problems and deliver solutions Work as a member of a team, helping the team respond quickly and effectively to business needs. Requirements B.Tech, M.Tech, or Ph.D. in Computer Science or related discipline 4-6 years of industry experience with a proven track record of ownership and delivery Experience formulating use cases as ML problems and putting ML models into production Solid grounding in core ML concepts and basic statistics Experience with software engineering of production-grade services in cloud environments handling data at large scale Desirable Cloud-based application and infrastructure deployment and management Common ML libraries (eg, scikit-learn, PyTorch) and components (eg, Airflow, MLFlow) Relevant cloud provider services (eg, AWS Sagemaker) LLM core concepts, libraries, and application design patterns Experience in multi-threaded programming and distributed systems Agile software development experience (test-driven development, iterative and incremental development) is a plus. About Us Sumo Logic, Inc., empowers the people who power modern, digital business. Sumo Logic enables customers to deliver reliable and secure cloud-native applications through its SaaS analytics platform. The Sumo Logic Continuous Intelligence Platform™ helps practitioners and developers ensure application reliability, secure and protect against modern security threats, and gain insights into their cloud infrastructures. Customers worldwide rely on Sumo Logic to get powerful real-time analytics and insights across observability and security solutions for their cloud-native applications. For more information, visit www.sumologic.com. Show more Show less

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate Job Description & Summary A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. Creating business intelligence from data requires an understanding of the business, the data, and the technology used to store and analyse that data. Using our Rapid Business Intelligence Solutions, data visualisation and integrated reporting dashboards, we can deliver agile, highly interactive reporting and analytics that help our clients to more effectively run their business and understand what business questions can be answered and how to unlock the answers. Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us. At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. " Job Description & Summary: A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. Creating business intelligence from data requires an understanding of the business, the data, and the technology used to store and analyse that data. Using our Rapid Business Intelligence Solutions, data visualisation and integrated reporting dashboards, we can deliver agile, highly interactive reporting and analytics that help our clients to more effectively run their business and understand what business questions can be answered and how to unlock the answers. Responsibilities ML engineer: 3-5 years of experience as AI/ML engineer or similar role. Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with model development and deployment processes. Proficiency in programming languages such as Python. Experience with data preprocessing, feature engineering, and model evaluation techniques. Familiarity with cloud platforms (e.g., AWS) and containerization (e.g., Docker, Kubernetes). Familiarity with version control systems (e.g., GitHub). Proficiency in data manipulation and analysis using libraries such as NumPy and Pandas. Good to have knowledge of deep learning, ML Ops: Kubeflow, MLFlow, Nextflow. Knowledge on text Analytics, NLP, Gen AI Mandatory Skill Sets Gen AI, Python Preferred Skill Sets Gen AI, Python Years Of Experience Required 3 - 5 Education Qualification B.Tech / M.Tech / MBA / MCA Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Master of Engineering, Master of Business Administration, Bachelor of Engineering Degrees/Field Of Study Preferred Certifications (if blank, certifications not specified) Required Skills Python (Programming Language) Optional Skills Desired Languages (If blank, desired languages not specified) Travel Requirements Not Specified Available for Work Visa Sponsorship? No Government Clearance Required? No Job Posting End Date Show more Show less

Join our applied-ML team to help turn data into product features—recommendation engines, predictive scores, and intelligent dashboards that ship to real users. You’ll prototype quickly, validate with metrics, and productionise models alongside senior ML engineers. Day-to-Day Responsibilities Clean, explore, and validate datasets (Pandas, NumPy, SQL) Build and evaluate ML/DL models (scikit-learn, TensorFlow / PyTorch) Develop reproducible pipelines using notebooks → scripts → Airflow / Kubeflow Participate in feature engineering, hyper-parameter tuning, and model-selection experiments Package and expose models as REST/gRPC endpoints; monitor drift & accuracy in prod Share insights with stakeholders through visualisations and concise reports Must-Have Skills 1–2 years building ML models in Python Solid understanding of supervised learning workflows (train/validate/test, cross-validation, metrics) Practical experience with at least one deep-learning framework (TensorFlow or PyTorch) Strong data-wrangling skills (Pandas, SQL) and basic statistics (A/B testing, hypothesis testing) Version-control discipline (Git) and comfort with Jupyter-based experimentation Good-to-Have Familiarity with MLOps tooling (MLflow, Weights & Biases, Sagemaker) Exposure to cloud data platforms (BigQuery, Snowflake, Redshift) Knowledge of NLP or CV libraries (spaCy, Hugging Face Transformers, OpenCV) Experience containerising ML services with Docker and orchestrating with Kubernetes Basic understanding of data-privacy and responsible-AI principles Job Types: Full-time, Permanent Pay: From ₹19,100.00 per month Benefits: Health insurance Life insurance Paid sick time Paid time off Provident Fund Schedule: Fixed shift Monday to Friday Experience: Junior Machine-Learning Engineer: 1 year (Preferred) Work Location: In person

Build and fine-tune Generative AI models (LLMs, diffusion models, etc.) for various applications. Work with agent and multi-agent frameworks to build task-specific or collaborative AI systems. Develop and deploy ML pipelines for training, inference, and evaluation. Collaborate with cross-functional teams (Product, Data Engineering, DevOps) to integrate ML models into products. Conduct data preprocessing, exploratory analysis, and feature engineering. Stay updated with state-of-the-art research in ML/GenAI and apply it to practical problems. Optimize models for performance, scalability, and efficiency. Work with APIs like OpenAI, AZURE OpenAI, and others for rapid prototyping and deployment. Contribute to internal tools and frameworks to support ML experimentation and monitoring. Required Skills & Qualifications Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or related field. 3 to 5 years of hands-on experience in Machine Learning and/or NLP projects. Proficiency in Python and popular ML libraries (e.g., PyTorch, TensorFlow, Hugging Face Transformers). Practical experience with agent and/or multi-agent frameworks (e.g., LangGraph, CrewAI, AutoGen, AutoGPT, BabyAGI, etc.) is highly desirable. Experience working with LLMs (GPT, Claude, etc.). Familiarity with prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning techniques. Strong understanding of data structures, algorithms, and ML concepts. Experience in deploying models using tools like Docker, FastAPI, Flask, or MLflow. Experience with vector databases (e.g., PG Vector, Pinecone, Weaviate). Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Airflow). Publications or contributions to open-source projects in ML/GenAI. Familiarity with ethical AI principles and responsible AI practices. Show more Show less

Role Overview Cloud Software Development Engineer with ability to design, develop, deploy, and maintain cloud-based applications and services, leveraging cloud platforms AWS and GCP focusing on scalability, security, and efficiency. About The Role Develop and deploy cloud-based distributed applications, ensuring they are efficient, secure, and scalable. Build and optimize large-scale data processing pipelines using Spark/pySpark, integrating with cloud-native services. Monitor the performance and health of cloud-based applications and infrastructure, ensuring they meet performance, scalability, and security standards. Collaborate with developers, SDETs, Researchers, DevOps engineers, and system administrators to ensure smooth development, deployment, and operations of data-driven applications. Implement data analytics and dashboarding solutions to support business intelligence, operational monitoring, and model performance tracking. Contribute to the development, deployment, and monitoring of machine learning models, with a clear understanding of the end-to-end ML lifecycle, including data collection, preprocessing, model (re)training, evaluation, deployment, and feedback loops. About You Proficient in programming languages such as Python and .NET, with experience Understanding of unit test frameworks in Python & .NET. Strong understanding of cloud platforms, particularly AWS and Google Cloud Platform (GCP), and their services. Solid grasp of AI and ML concepts, tools (MLFlow etc), and best practices. Understanding of end-to-end ML lifecycle and workflows in production-grade environments. Knowledge of cloud security best practices and the ability to implement them in application and infrastructure design. Familiarity with containerization and orchestration technologies such as Docker and Kubernetes. Competent in working with both relational and non-relational databases to support dynamic application needs. Company Overview McAfee is a leader in personal security for consumers. Focused on protecting people, not just devices, McAfee consumer solutions adapt to users’ needs in an always online world, empowering them to live securely through integrated, intuitive solutions that protects their families and communities with the right security at the right moment. Company Benefits And Perks We work hard to embrace diversity and inclusion and encourage everyone at McAfee to bring their authentic selves to work every day. We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees. Bonus Program Pension and Retirement Plans Medical, Dental and Vision Coverage Paid Time Off Paid Parental Leave Support for Community Involvement We're serious about our commitment to diversity which is why McAfee prohibits discrimination based on race, color, religion, gender, national origin, age, disability, veteran status, marital status, pregnancy, gender expression or identity, sexual orientation or any other legally protected status. Show more Show less

Job Title: Senior AI Developer – Computer Vision & LLMs Location: Coimbatore, Work from office role Experience Required: 4+ years Employment Type: Full-Time, Permanent Company: Katomaran Technologies About Us Katomaran Technologies is a cutting-edge technology company building real-world AI applications that span across computer vision, large language models (LLMs), and AI agentic systems. We are looking for a highly motivated Senior AI Developer who thrives at the intersection of technology, leadership, and innovation. You will play a core role in architecting AI products , leading engineering teams , and collaborating directly with the founding team and customers to turn vision into scalable, production-ready solutions. Key Responsibilities Architect and develop scalable AI solutions using computer vision, LLMs, and agent-based AI architectures. Collaborate with the founding team to define product roadmaps and AI strategy. Lead and mentor a team of AI and software engineers, ensuring high code quality and project delivery timelines. Develop robust, efficient pipelines for model training, validation, deployment, and real-time inference. Work closely with customers and internal stakeholders to translate requirements into AI-powered applications. Stay up to date with state-of-the-art research in vision models (YOLO, SAM, CLIP, etc.), transformers, and agentic systems (AutoGPT-style orchestration). Optimize AI models for deployment on cloud and edge environments. Required Skills & Qualifications Bachelor’s or Master’s in Computer Science, AI, Machine Learning, or related fields. 5+ years of hands-on experience building AI applications in computer vision and/or NLP. Strong knowledge of Deep Learning frameworks (PyTorch, TensorFlow, OpenCV, HuggingFace, etc.). Proven experience with LLM fine-tuning, prompt engineering , and embedding-based retrieval (RAG) . Solid understanding of agentic systems such as LangGraph, CrewAI, AutoGen, or custom orchestrators. Ability to design and manage production-grade AI systems (Docker, REST APIs, GPU optimization, etc.). Strong communication and leadership skills, with experience managing small to mid-size teams. Startup mindset – self-driven, ownership-oriented, and comfortable in ambiguity. Nice to Have Experience with video analytics platforms or edge deployment (Jetson, Coral, etc.). Experience with programming skills in C++ will be an added advantage Knowledge of MLOps practices and tools (MLflow, Weights & Biases, ClearML, etc.). Exposure to Reinforcement Learning or multi-agent collaboration models. Customer-facing experience or involvement in AI product strategy. What We Offer Medical insurance Paid sick time Paid time off PF To Apply: Send your resume, GitHub/portfolio, and a brief note about your most exciting AI project to hr@katomaran.com. Job Type: Full-time Pay: Up to ₹600,000.00 per year Benefits: Health insurance Paid sick time Paid time off Provident Fund Schedule: Day shift Ability to commute/relocate: Peelamedu, Coimbatore, Tamil Nadu: Reliably commute or planning to relocate before starting work (Required) Education: Bachelor's (Required) Experience: AI applications: 5 years (Required) LLM: 5 years (Required) Work Location: In person

Date: 4 Jun 2025 Company: Qualitest Group Country/Region: IN Key Responsibilities Design, develop, and deploy ML models and AI solutions across various domains such as NLP, computer vision, recommendation systems, time-series forecasting, etc. Perform data preprocessing, feature engineering, and model training using frameworks like TensorFlow, PyTorch, Scikit-learn, or similar. Collaborate with cross-functional teams to understand business problems and translate them into AI/ML solutions. Optimize models for performance, scalability, and reliability in production environments. Integrate ML pipelines with production systems using tools like MLflow, Airflow, Docker, or Kubernetes. Conduct rigorous model evaluation using metrics and validation techniques. Stay up-to-date with state-of-the-art AI/ML research and apply findings to enhance existing systems. Mentor junior engineers and contribute to best practices in ML engineering. Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. 4–8 years of hands-on experience in machine learning, deep learning, or applied AI. Proficiency in Python and ML libraries/frameworks (e.g., Scikit-learn, TensorFlow, PyTorch, XGBoost). Experience with data wrangling tools (Pandas, NumPy) and SQL/NoSQL databases. Familiarity with cloud platforms (AWS, GCP, or Azure) and ML tools (SageMaker, Vertex AI, etc.). Solid understanding of model deployment, monitoring, and CI/CD pipelines. Strong problem-solving skills and the ability to communicate technical concepts clearly.

Indore, India Job Description : Full-time, On-site Role 5+ years of experience as an AI/ML Engineer Atleast 2+ years in a leadership or team-building role Experience in building powerful, real-world applications across various domains Strong communication skills and the ability to explain complex AI concepts to business stakeholders and clients. Experience in leading small to mid-sized teams. A product-first mindset and the ability to drive initiatives from idea to production. Passion for staying at the cutting edge of AI — especially in the era of LLMs and generative AI. Work in a collaborative, high-ownership, fast-moving tech environment You’ll be setting up the AI engine for a company already trusted for its tech excellence. If you’re seeking technical autonomy, client-facing impact, and team-building ownership , this is your place. Responsibilities : Lead the design, development, and deployment of AI/ML and Deep Learning models. Hire, train, and mentor a growing team of AI/ML engineers and data scientists. Own the architecture and tech stack decisions for the AI division. Engage in client discovery calls and pre-sales conversations to convert technical insights into business opportunities. Lead PoC development, client interviews, and project planning in collaboration with internal and external stakeholders. Stay updated with the latest in AI/ML (especially LLMs, vector search, generative AI, multi-agent chatbot) and translate advancements into real-world implementations. Qualifications : Bachelor’s or Master's degree in CS/IT / AI-ML / Data Science Python, NumPy, Pandas, Scikit-learn, PySpark Deep Learning: TensorFlow, PyTorch, Keras CNNs, RNNs, Attention Mechanisms, Transformers SVD (Singular Value Decomposition), KMean, Recency weight Text embeddings, semantic search, vector DBs (FAISS, Pinecone, Weaviate) Model Context Protocol (MCP) Model Lifecycle: Data preprocessing, training, tuning, evaluation (ROC, F1, AUC, confusion matrix) Botpress / Copilot Studio workflow and integration experience Deployment: RESTful ML APIs, Docker, AWS/GCP (SageMaker, Vertex AI), model versioning Workflow Tools: MLflow, Azure ML, Airflow, Git-based CI/CD Creating Rest APIs using FastAPI framework or equivalent Experience: 5+ yrs

Job Listing Detail Summary Gainwell is seeking LLM Ops Engineers and ML Ops Engineers to join our growing AI/ML team. This role is responsible for developing, deploying, and maintaining scalable infrastructure and pipelines for Machine Learning (ML) models and Large Language Models (LLMs). You will play a critical role in ensuring smooth model lifecycle management, performance monitoring, version control, and compliance while collaborating closely with Data Scientists, DevOps. Your role in our mission Core LLM Ops Responsibilities: Develop and manage scalable deployment strategies specifically tailored for LLMs (GPT, Llama, Claude, etc.). Optimize LLM inference performance, including model parallelization, quantization, pruning, and fine-tuning pipelines. Integrate prompt management, version control, and retrieval-augmented generation (RAG) pipelines. Manage vector databases, embedding stores, and document stores used in conjunction with LLMs. Monitor hallucination rates, token usage, and overall cost optimization for LLM APIs or on-prem deployments. Continuously monitor models for its performance and ensure alert system in place. Ensure compliance with ethical AI practices, privacy regulations, and responsible AI guidelines in LLM workflows. Core ML Ops Responsibilities: Design, build, and maintain robust CI/CD pipelines for ML model training, validation, deployment, and monitoring. Implement version control, model registry, and reproducibility strategies for ML models. Automate data ingestion, feature engineering, and model retraining workflows. Monitor model performance, drift, and ensure proper alerting systems are in place. Implement security, compliance, and governance protocols for model deployment. Collaborate with Data Scientists to streamline model development and experimentation. What we're looking for Bachelor's/Master’s degree in computer science, Engineering, or related fields. Strong experience with ML Ops tools (Kubeflow, MLflow, TFX, SageMaker, etc.). Experience with LLM-specific tools and frameworks (LangChain,Lang Graph, LlamaIndex, Hugging Face, OpenAI APIs, Vector DBs like Pinecone, FAISS, Weavite, Chroma DB etc.). Solid experience in deploying models in cloud (AWS, Azure, GCP) and on-prem environments. Proficient in containerization (Docker, Kubernetes) and CI/CD practices. Familiarity with monitoring tools like Prometheus, Grafana, and ML observability platforms. Strong coding skills in Python, Bash, and familiarity with infrastructure-as-code tools (Terraform, Helm, etc.).Knowledge of healthcare AI applications and regulatory compliance (HIPAA, CMS) is a plus. Strong skills in Giskard, Deepeval etc. What you should expect in this role Fully Remote Opportunity – Work from anywhere in the India Minimal Travel Required – Occasional travel opportunities (0-10%). Opportunity to Work on Cutting-Edge AI Solutions in a mission-driven healthcare technology environment. Show more Show less

Looking for Enterprise data platform admin to implement and maintain the Databricks platform on AWS. Person should have passion to work in agile environment and the experience in supporting databricks platform on AWS. Responsibilities Platform Administration: Implement and maintain the Databricks platform, including workspace setup, user and group management, access control, and security configurations. Operational Support: Provide technical support to data engineering, data science, and application teams. Perform restores/recoveries, troubleshoot service issues, and resolve platform-related problems. Cluster Management: Install, configure, and maintain Databricks clusters and workspaces. Monitor and manage cluster performance, resource utilization, and platform costs. Security and Compliance: Implement and manage access controls and security policies to protect sensitive data. Ensure compliance with relevant data governance and regulatory requirements. Integration: Manage and maintain connections between Databricks and other data sources like Snowflake. Optimize data pipelines and workflows. Automation: Develop and maintain automation scripts and tools for platform provisioning and routine tasks using Terraform. Required Skills Experience: 3+ years of production support of the Databricks platform. Technical Expertise Terraform, AWS cloud services, Databricks administration AWS IAM, VPC, private endpoints, firewalls, S3 and knowledge on how Databricks integrates with them MLflow, Workflows, Databricks Asset Bundles Databricks REST API: For automation, scripting, and integration dbx CLI: For CI/CD integration Delta Live Tables (DLT): For managing streaming and batch pipelines SQL + PySpark skills to debug and support. Preferred Skills: Databricks certification Show more Show less

Looking for Enterprise data platform admin to implement and maintain the Databricks platform on AWS. Person should have passion to work in agile environment and the experience in supporting databricks platform on AWS. Responsibilities Platform Administration: Implement and maintain the Databricks platform, including workspace setup, user and group management, access control, and security configurations. Operational Support: Provide technical support to data engineering, data science, and application teams. Perform restores/recoveries, troubleshoot service issues, and resolve platform-related problems. Cluster Management: Install, configure, and maintain Databricks clusters and workspaces. Monitor and manage cluster performance, resource utilization, and platform costs. Security and Compliance: Implement and manage access controls and security policies to protect sensitive data. Ensure compliance with relevant data governance and regulatory requirements. Integration: Manage and maintain connections between Databricks and other data sources like Snowflake. Optimize data pipelines and workflows. Automation: Develop and maintain automation scripts and tools for platform provisioning and routine tasks using Terraform. Required Skills Experience: 3+ years of production support of the Databricks platform. Technical Expertise Terraform, AWS cloud services, Databricks administration AWS IAM, VPC, private endpoints, firewalls, S3 and knowledge on how Databricks integrates with them MLflow, Workflows, Databricks Asset Bundles Databricks REST API: For automation, scripting, and integration dbx CLI: For CI/CD integration Delta Live Tables (DLT): For managing streaming and batch pipelines SQL + PySpark skills to debug and support. Preferred Skills: Databricks certification Show more Show less

As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Job Reference: Role Summary: The AI/ML Platform Engineering Lead is a pivotal leadership role responsible for managing the day-to-day operations and development of the AI/ML platform team. In this role, you will guide the team in designing, building, and maintaining scalable platforms, while collaborating with other engineering and data science teams to ensure successful model deployment and lifecycle management. Key Responsibilities: Lead and manage a team of platform engineers in developing and maintaining robust AI/ML platforms Define and implement best practices for machine learning infrastructure, ensuring scalability, performance, and security Collaborate closely with data scientists and DevOps teams to optimize the ML lifecycle from model training to deployment Establish and enforce standards for platform automation, monitoring, and operational efficiency Serve as the primary liaison between engineering teams, product teams, and leadership Mentor and develop junior engineers, providing technical guidance and performance feedback Stay abreast of the latest advancements in AI/ML infrastructure and integrate new technologies where applicable Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field 8+ years of experience in AI/ML platform development and infrastructure Proven experience in leading engineering teams and driving large-scale projects Extensive expertise in cloud infrastructure (AWS, GCP, Azure), MLOps tools (e.g., Kubeflow, MLflow), and infrastructure as code (Terraform) Strong programming skills in Python and Node.js, with a proven track record of building scalable and maintainable systems that support AI/ML workflows Hands-on experience with monitoring and observability tools, such as Datadog, to ensure platform reliability and performance Strong leadership and communication skills with the ability to influence cross-functional teams Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment Show more Show less

About ViewTrade: ViewTrade is the force that powers fintech and cross-border investing for financial services firms throughout the world. We provide the technology, support and brokerage services that business innovators need to quickly launch or enhance a retail, fintech, wealth, or cross boarder investing experience. Now in our third decade, our approach has helped 300+ firms – from technology startups to large banks, brokers, super apps, advisory, and wealth management – create the differentiating investment experiences their customer’s demand. With clients in over 29 countries and a team that brings decades of experience and understanding of financial services technology and services, we help our business clients deliver the investment access and financial solutions they require. Our Values: Expertise Integrity Solution Driven. Teamwork Long Term success Always winning Always learning Job Summary: Seeking an experienced Cloud Solutions Architect to design and oversee robust, scalable, secure, and cost-effective multi-cloud and hybrid (on-prem) infrastructure solutions. This role requires deep expertise in AI, particularly Generative AI workloads, and involves translating business needs into technical designs, providing technical leadership, and ensuring best practices across diverse environments . Key Responsibilities: Design and architect complex solutions across multi-cloud and hybrid (on-prem) environments (preferably AWS). Translate business/technical requirements into clear architectural designs and documentation. Develop cloud and hybrid adoption strategies and roadmaps. Architect infrastructure and data pipelines for AI/ML and Generative AI workloads (compute, storage, MLOps). Design on-premise to cloud/hybrid migration plans. Evaluate and recommend cloud services and technologies across multiple providers. Define and enforce architectural standards (security, cost, reliability). Provide technical guidance and collaborate with engineering, ops, and security teams. Architect third-party integrations and collaborate on cybersecurity initiatives. Required Qualifications: Around 12+ years IT experience with 5+ years as a Cloud/Solutions Architect role Proven experience architecting/implementing solutions on at least two major public cloud platforms (e.g., AWS, Azure, GCP). AWS preferred. Strong hybrid (on-prem) and migration experience. Demonstrated experience architecting infrastructure for AI/ML/GenAI workloads (compute, data, deployment patterns). Deep understanding of cloud networking, security, and cost optimization. Proficiency in IaC (Terraform/CloudFormation/ARM), containers (Docker/Kubernetes), serverless. Familiarity with FinOps concepts. Excellent communication and problem-solving skills. Preferred Qualifications: Experience with cloud cost management and optimization strategies (FinOps) in a multi-setup environment. Experience with specific GenAI && MLOps platforms and tools ( OpenAI, Google AI, hugging face, Github Co-pilot , AWS sagemaker, AWS Bedrock, MLflow, Kubeflow, Feast, ZenML ) Good understanding of on-premise data center architecture, infrastructure (compute, storage, networking), virtualization, and experience designing and implementing hybrid cloud solutions and on-premise to cloud migration strategies. Experience in the Fintech industry. What does ViewTradebring to the table : Opportunity to do what your current firm may be hesitant to do. An informal and self-managed work culture. Freedom to experiment with new ideas and technologies. A highly motivating work environment where you learn exponentially and grow with the organization. An opportunity to create an impact at scale. Location: GIFT CITY, Gandhinagar Experience: 12+ years We are an equal opportunity employer and all qualified applicants will receive consideration for employment withoutregard to race, color, religion,sex, disability status,or any other characteristic protected by the law. Show more Show less

Job Title: Technology Analyst Experience: 4+ Years Job Level: JL4A Location: Bangalore / Pune Salary: Up to ₹20 LPA Type: Full-Time Job Summary We are seeking a skilled Technology Analyst with strong hands-on experience in Generative AI and Machine Learning (ML) to join our dynamic team. The ideal candidate will be responsible for driving innovation through AI-based solutions, model development, and implementation across projects. Mandatory Skills 4+ years of experience in AI/ML development and deployment Hands-on experience with Generative AI frameworks (e.g., GPT, BERT, LLaMA) Strong Python programming with libraries such as TensorFlow, PyTorch, Hugging Face Practical experience building and fine-tuning ML/DL models Experience in prompt engineering and working with LLMs (Large Language Models) Primary Skills Strong understanding of NLP, computer vision, or recommendation systems Model training, evaluation, tuning, and deployment Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI Experience in building APIs to serve AI/ML models Data preprocessing and feature engineering techniques Cloud exposure (AWS/GCP/Azure) for AI model deployment Secondary Skills Familiarity with containerization (Docker, Kubernetes) Experience with CI/CD pipelines Basic understanding of front-end integration of AI models (e.g., through REST APIs) Exposure to Data Engineering or BI tools is a plus Knowledge of Data Privacy, Model Explainability, and Ethical AI principles Good To Have Published research papers or contributions to open-source AI/ML projects Certification in AI/ML or Gen AI technologies Role Expectations Collaborate with cross-functional teams to define AI solutions Develop, test, and deploy Gen AI models in production Ensure scalability, accuracy, and performance of AI solutions Provide guidance and mentorship to junior developers when needed Skills: generative ai,llms,tensorflow,nlp,mlops,feature engineering,vertex ai,pytorch,tensor flow,pytouch,apis,data preprocessing,computer vision,technology,ai/ml,mlflow,recommendation systems,kubernetes,docker,kubeflow,aws,python,azure,gcp,machine learning,hugging face,ci/cd Show more Show less