30 Ml Engineering Jobs

As a Machine Learning Engineer at Skyfall, you will play a crucial role in deploying and optimizing large language models (LLMs) in production environments. Your responsibilities will include deploying post-trained LLMs, optimizing inference for cost and latency, and building scalable training pipelines using cutting-edge technologies like DeepSpeed, Accelerate, and Ray. The Skyfall team, comprising of industry pioneers from Maluuba, is committed to revolutionizing the AI ecosystem by creating the first world model for the enterprise. By overcoming the limitations of existing LLMs, the Enterprise World Model aims to provide enterprises with a comprehensive understanding of the intricate relationships between data, people, and processes within organizations. You will be part of a dynamic team spread across New York, Toronto, and Bangalore, working on designing distributed training infrastructure, managing multi-cloud ML deployments, and implementing advanced model compression techniques. Additionally, you will develop internal tools to facilitate multi-GPU training and large-scale experimentation, ensuring efficient resource allocation and continuous model evaluation. To excel in this role, you should have a minimum of 3 years of experience in ML engineering, model deployment, and large-scale training. Proficiency in vector databases such as FAISS, Pinecone, and Weaviate for retrieval-augmented generation (RAG) is essential. Experience with multi-cloud ML deployment, hands-on deployment of large-scale models in production, and expertise in multi-GPU training and inference optimizations are key requirements. Your strong knowledge of ML system performance tuning, latency optimization, and cost reduction strategies will be instrumental in developing cluster management tools for external compute infrastructure and implementing state-of-the-art model compression techniques. By staying abreast of LLM fine-tuning techniques, RLHF, and model evaluation metrics, you will contribute to Skyfall's mission of disrupting the AI landscape and providing enterprises with significant value through innovative solutions.,

It is exciting to be part of a company where individuals wholeheartedly BELIEVE in the mission! The company is dedicated to bringing enthusiasm and a customer-centric approach to the operations. As a Data Scientist, you will be required to work on the end-to-end data science pipeline, demonstrating the ability to meticulously design efficient data models, training data samples, training pipelines, and inference pipelines to ensure reproducibility. You should possess a strong background in evaluating various AI/ML outputs and models such as recommender systems, similarity scoring, classification, and regression. Your role will involve breaking down complex business challenges into manageable sub-tasks that can be addressed with AI/ML solutions to facilitate decision-making at scale. A solid understanding of statistical concepts and empirical methods that influence post-modeling decisions like sorting, ranking, and selection is essential. You must have substantial experience in transitioning Proof of Concepts (PoCs) and experimental models into production-grade AIML systems. Collaborating effectively with ML engineering and MLOps teams is crucial to deploying AI/ML models, constructing and serving models through APIs, and integrating AI/ML models into web applications. The role requires the ability to lead mid-sized teams, strategize project tracks centered around AI/ML and data science, and strike a balance between delegation and hands-on development. Applying a first-principles approach to tackle data science problems, communicating data requirements to data engineering teams, and elucidating model outputs to business users are key responsibilities. Engaging with business users to comprehend requirements and translating them into technical data science challenges is imperative. Effectively communicating and translating model algorithms and outputs to non-technical users and stakeholders is expected. Proficiency in agile methodologies and project management practices is essential. Creating efficient user stories and other agile project artifacts should come naturally. If you thrive in a dynamic environment and enjoy collaborating with enthusiastic high-achievers, a rewarding career opportunity awaits you here! If this opportunity does not align with your current aspirations, please express your interest in future openings by clicking on Introduce Yourself in the top-right corner of the page or setting up email alerts for relevant job postings.,

As a ML Specialist GenAI at Claidroid Technologies Pvt. Ltd., your primary responsibility will be to design, develop, and deploy scalable Generative AI systems. This role involves implementing LLM agents, RAG architectures, and MLOps pipelines, and managing the full GenAI product lifecycle. You will lead AI developers, build solutions using LLMs, Diffusion Models, and GenAI agents, and fine-tune models with LangChain, LangGraph, and promptflow. Deployment will utilize Azure, containerization, and CI/CD practices. It will be your duty to ensure model observability, optimize performance and cost, apply ethical AI principles, and effectively communicate insights to stakeholders. This position is based in Pune/Trivandrum with options for WFH/Hybrid, working from 11 AM to 8 PM IST, suitable for candidates with under a 30-day notice period. To excel in this role, you should possess 5-10 years of experience in ML Engineering and Generative AI. Proficiency in technologies like LLMs, RAG, Prompt Engineering, LangChain, LangGraph, promptflow, and Autogen is essential. Strong skills in Python, PyTorch/TensorFlow, FastAPI, and AsyncIO are required. Experience with CI/CD pipelines (specifically GitHub Actions), Docker, Kubernetes, Azure cloud services (preferred), or AWS/GCP is advantageous. Additionally, expertise in MLOps, model deployment, monitoring, performance tuning, and understanding of Responsible AI principles, bias mitigation, and model explainability are crucial for this role. Claidroid Technologies is a leader in digital transformation, specializing in Enterprise Service Management and Enterprise Security Management solutions. With headquarters in India and offices in Helsinki, Finland, and the USA, we aim to deliver bespoke services to a wider audience globally. Joining our team offers competitive compensation, a hybrid working model, generous benefits such as comprehensive health insurance and performance bonuses, as well as ample opportunities for career growth in a dynamic and innovative environment. Be part of our collaborative and inclusive work culture that values your contributions and supports your professional development.,

Agoda is an online travel booking platform for accommodations, flights, and more. The company builds and deploys cutting-edge technology to connect travelers with a global network of 4.7M hotels and holiday properties worldwide, along with flights, activities, and other travel services. As part of Booking Holdings and with 7,100+ employees representing 95+ nationalities in 27 markets, Agoda fosters a work environment rich in diversity, creativity, and collaboration. The company values innovation through a culture of experimentation and ownership to enhance the customer experience of exploring the world. Agoda's purpose is to bridge the world through travel, believing that travel enables people to enjoy, learn, and experience the amazing world we live in. It brings individuals and cultures closer together, fostering empathy, understanding, and happiness. The Data department at Agoda oversees all data-related requirements to enable and increase the utilization of data within the company. The department implements resources such as operational and analytical databases, queue systems, BI tools, and data science technology. The team is composed of skilled, driven, and diverse individuals from around the globe, working together to empower decision-making processes for business users, product managers, engineers, and other stakeholders. The Data team is dedicated to improving the search experience for customers with faster results and ensuring protection against fraudulent activities. As an ML Technical Product Manager at Agoda, you will play a crucial role in empowering employees with the tools necessary to make informed decisions and develop cutting-edge features and models for end users. You will be responsible for internal product requirements, analysis, ideation, feature design, roadmap development, project management, trainings, and ensuring the quality of solutions. The role involves conceptualizing platform capabilities to enhance external customer experiences and contribute to Agoda's goal of being a data-driven company. In this role, you will own the product lifecycle from concept to design, implementation, and analysis. You will gather and synthesize requirements from various stakeholders, lead discussions with internal customers, demonstrate strong leadership and organizational skills, and bridge the gap between business and technical aspects effectively. The ideal candidate should have technical experience in ML engineering, data science, or related roles, along with experience in technical program/product management in a fast-paced environment. Excellent interpersonal, presentation, and organizational skills are essential, as well as the ability to communicate effectively with both business and technical teams. This position requires the candidate to relocate fully to Bangkok, Thailand, where relocation support will be provided. Agoda is an Equal Opportunity Employer. Your application will be kept on file for future vacancies, and you can request to have your details removed at any time. Agoda does not accept third-party resumes and is not responsible for any fees related to unsolicited resumes.,

ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it, our most valuable asset is our people. Here you'll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers, and consumers, worldwide. ZSers drive impact by bringing a client-first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning, bold ideas, courage, and passion to drive life-changing impact to ZS. At ZS, we honor the visible and invisible elements of our identities, personal experiences, and belief systemsthe ones that comprise us as individuals, shape who we are, and make us unique. We believe your personal interests, identities, and desire to learn are part of your success here. Learn more about our diversity, equity, and inclusion efforts and the networks ZS supports to assist our ZSers in cultivating community spaces, obtaining the resources they need to thrive, and sharing the messages they are passionate about. ZS's Beyond Healthcare Analytics (BHCA) Team is shaping one of the key growth vector areas for ZS, Beyond Healthcare engagement, comprising clients from industries like Quick service restaurants, Technology, Food & Beverage, Hospitality, Travel, Insurance, Consumer Products Goods & other such industries across North America, Europe & South East Asia region. The BHCA India team currently has a presence across New Delhi, Pune, and Bengaluru offices and is continuously expanding further at a great pace. The BHCA India team works with colleagues across clients and geographies to create and deliver real-world pragmatic solutions leveraging AI SaaS products & platforms, Generative AI applications, and other Advanced analytics solutions at scale. What You'll Do: - Build, Refine and Use ML Engineering platforms and components. - Scaling machine learning algorithms to work on massive datasets and strict SLAs. - Build and orchestrate model pipelines including feature engineering, inferencing, and continuous model training. - Implement ML Ops including model KPI measurements, tracking, model drift & model feedback loop. - Collaborate with client-facing teams to understand business context at a high level and contribute to technical requirement gathering. - Implement basic features aligning with technical requirements. - Write production-ready code that is easily testable, understood by other developers, and accounts for edge cases and errors. - Ensure the highest quality of deliverables by following architecture/design guidelines, coding best practices, periodic design/code reviews. - Write unit tests as well as higher-level tests to handle expected edge cases and errors gracefully, as well as happy paths. - Use bug tracking, code review, version control, and other tools to organize and deliver work. - Participate in scrum calls and agile ceremonies, and effectively communicate work progress, issues, and dependencies. - Consistently contribute to researching & evaluating the latest architecture patterns/technologies through rapid learning, conducting proof-of-concepts, and creating prototype solutions. What You'll Bring: - A master's or bachelor's degree in Computer Science or related field from a top university. - 4+ years hands-on experience in ML development. - Good understanding of the fundamentals of machine learning. - Strong programming expertise in Python, PySpark/Scala. - Expertise in crafting ML Models for high performance and scalability. - Experience in implementing feature engineering, inferencing pipelines, and real-time model predictions. - Experience in ML Ops to measure and track model performance, experience working with MLFlow. - Experience with Spark or other distributed computing frameworks. - Experience in ML platforms like Sage maker, Kubeflow. - Experience with pipeline orchestration tools such as Airflow. - Experience in deploying models to cloud services like AWS, Azure, GCP, Azure ML. - Expertise in SQL, SQL DB's. - Knowledgeable of core CS concepts such as common data structures and algorithms. - Collaborate well with teams with different backgrounds/expertise/functions. Perks & Benefits: ZS offers a comprehensive total rewards package including health and well-being, financial planning, annual leave, personal growth, and professional development. Our robust skills development programs, multiple career progression options, internal mobility paths, and collaborative culture empower you to thrive as an individual and global team member. We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections. Travel: Travel is a requirement at ZS for client-facing ZSers; business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures. Considering applying At ZS, we're building a diverse and inclusive company where people bring their passions to inspire life-changing impact and deliver better outcomes for all. We are most interested in finding the best candidate for the job and recognize the value that candidates with all backgrounds, including non-traditional ones, bring. If you are interested in joining us, we encourage you to apply even if you don't meet 100% of the requirements listed above. ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law. To Complete Your Application: Candidates must possess or be able to obtain work authorization for their intended country of employment. An online application, including a full set of transcripts (official or unofficial), is required to be considered. NO AGENCY CALLS, PLEASE.,

As a LLM Engineer at HuggingFace, you will play a crucial role in bridging the gap between advanced language models and real-world applications. Your primary focus will be on fine-tuning, evaluating, and deploying LLMs using frameworks such as HuggingFace and Ollama. You will be responsible for developing React-based applications with seamless LLM integrations through REST, WebSockets, and APIs. Additionally, you will work on building scalable pipelines for data extraction, cleaning, and transformation, as well as creating and managing ETL workflows for training data and RAG pipelines. Your role will also involve driving full-stack LLM feature development from prototype to production. To excel in this position, you should have at least 2 years of professional experience in ML engineering, AI tooling, or full-stack development. Strong hands-on experience with HuggingFace Transformers and LLM fine-tuning is essential. Proficiency in React, TypeScript/JavaScript, and back-end integration is required, along with comfort working with data engineering tools such as Python, SQL, and Pandas. Familiarity with vector databases, embeddings, and LLM orchestration frameworks is a plus. Candidates with experience in Ollama, LangChain, or LlamaIndex will be given bonus points. Exposure to real-time LLM applications like chatbots, copilots, or internal assistants, as well as prior work with enterprise or SaaS AI integrations, are highly valued. This role offers a remote-friendly environment with flexible working hours and a high-ownership opportunity. Join our small, fast-moving team at HuggingFace and be part of building the next generation of intelligent systems. If you are passionate about working on impactful AI products and have the drive to grow in this field, we would love to hear from you.,

At Uber, we reimagine the way the world moves for the better. The Uber AI Solutions organization, also known as Global Scaled Solutions, is at the forefront of enabling various operations and technologies to support this mission. Our capabilities include data annotation for AI/ML innovation, app testing, localization/internationalization, map editing, data analytics, engineering, and more. We leverage a combination of technology and human intelligence to efficiently run scaled programs. Within Uber AI Solutions, we focus on delivering high-quality scaled programs in operations, technology, and data analytics for different Uber businesses. We utilize our extensive vendor partner network to execute these programs effectively. Moreover, we aim to expand our impact beyond Uber by offering tech and operations solutions that can help enterprises worldwide accelerate their data, AI, and product initiatives. Through online tasks, we create flexible earning opportunities for millions of individuals globally. Our unique combination of technology, operations expertise, and knowledge work platform positions us as a leading human-in-the-loop solution provider in the industry. About The Role We are seeking an exceptional candidate to drive and oversee programs related to AI training and evaluations within the Engineering Services team of Uber AI Solutions. This role specifically focuses on coding/engineering, agentic AI, data analytics, and related fields. The candidate will have the opportunity to enhance and scale existing capabilities for coding and data applications in AI training, establishing Uber AI Solutions as a leader in data annotation and AI training. What You Will Do - Lead multiple annotation/training/evaluation programs for clients, focusing on coding and data areas - Develop delivery solutions based on client requirements, including sourcing technical talent and managing service delivery quality checks - Engage with client stakeholders to shape project scope, demonstrate capabilities, and ensure successful project governance - Collaborate with Sales to interact with clients and design delivery solutions - Implement a sourcing strategy to acquire technical talent for coding and data-related training/evaluations - Work with Product and Engineering teams to develop tech platform capabilities specific to coding and data analytics tasks - Demonstrate expertise in coding and data analytics AI training/evaluations during client engagements and drive talent supply strategy and platform development - Coach and mentor the program manager team to enhance in-house talent for coding and data AI evaluations/training - Represent coding and data AI capabilities at senior leadership interactions and drive sponsorship for initiatives - Continually improve work processes, enhance delivery maturity, and promote organizational culture What You Will Need - 10+ years of experience in software engineering, ML engineering, and ML operations - Experience in managing delivery services for data annotation, training, and evaluation in coding and development fields - Familiarity with client-facing service management, solutioning, and talent sourcing strategies - Strong communication skills for engaging with senior management and cross-functional teams - Track record of driving innovation and thought leadership in AI/ML training and evaluation services - Ability to collaborate effectively across teams and drive impact in a global organization - Experience in mentoring and coaching team members to facilitate organizational growth,

As an Associate Data Architect at Quantiphi, you will be part of a dynamic team that thrives on innovation and growth. Your role will involve designing and delivering big data pipelines for structured and unstructured data across diverse geographies, particularly focusing on assisting healthcare organizations in achieving their business objectives through the utilization of data ingestion technologies, cloud services, and DevOps practices. Your responsibilities will include collaborating with cloud engineers and clients to address large-scale data challenges by creating tools for migration, storage, and processing on Google Cloud. You will be instrumental in crafting cloud migration strategies for both cloud-based and on-premise applications, as well as diagnosing and resolving complex issues within distributed systems to enhance efficiency at scale. In this role, you will have the opportunity to design and implement cutting-edge solutions for data storage and computation for various clients. You will work closely with experts from different domains such as Cloud engineering, Software engineering, and ML engineering to develop platforms and applications that align with the evolving trends in the healthcare sector, including digital diagnosis, AI marketplace, and software as a medical product. Effective communication with cross-functional teams, including Infrastructure, Network, Engineering, DevOps, SiteOps, and cloud customers, will be essential to drive successful project outcomes. Additionally, you will play a key role in building advanced automation tools, monitoring solutions, and data operations frameworks across multiple cloud environments to streamline processes and enhance operational efficiency. A strong understanding of data modeling and governance principles will be crucial for this role, enabling you to contribute meaningfully to the development of scalable and sustainable data architectures. If you thrive in a fast-paced environment that values innovation, collaboration, and continuous learning, then a career as an Associate Data Architect at Quantiphi is the perfect fit for you. Join us and be part of a team of dedicated professionals who are passionate about driving positive change through technology and teamwork.,

As a part of ZS, you will have the opportunity to work in a place driven by passion that aims to change lives. ZS is a management consulting and technology firm that is dedicated to enhancing life and its quality. The core strength of ZS lies in its people, who work collectively to develop transformative solutions for patients, caregivers, and consumers worldwide. By adopting a client-first approach, ZS employees bring impactful results to every engagement by partnering closely with clients to design custom solutions and technological products that drive value and yield positive outcomes in key areas of their business. Your role at ZS will require you to bring inquisitiveness for learning, innovative ideas, courage, and dedication to make a life-changing impact. At ZS, the individuals are highly valued, recognizing both the visible and invisible facets of their identities, personal experiences, and belief systems. These elements shape the uniqueness of each individual and contribute to the diverse tapestry within ZS. ZS acknowledges and celebrates personal interests, identities, and the thirst for knowledge as integral components of success within the organization. Learn more about the diversity, equity, and inclusion initiatives at ZS, along with the networks that support ZS employees in fostering community spaces, accessing necessary resources for growth, and amplifying the messages they are passionate about. As an Architecture & Engineering Specialist specializing in ML Engineering at ZS's India Capability & Expertise Center (CEC), you will be part of a team that constitutes over 60% of ZS employees across three offices in New Delhi, Pune, and Bengaluru. The CEC plays a pivotal role in collaborating with colleagues from North America, Europe, and East Asia to deliver practical solutions to clients that drive the company's operations. Upholding standards of analytical, operational, and technological excellence, the CEC leverages collective knowledge to enable ZS teams to achieve superior outcomes for clients. Joining ZS's Scaled AI practice within the Architecture & Engineering Expertise Center will immerse you in a dynamic ecosystem focused on generating continuous business value for clients through innovative machine learning, deep learning, and engineering capabilities. In this role, you will collaborate with data scientists to craft cutting-edge AI models, develop and utilize advanced ML platforms, establish and implement sophisticated ML pipelines, and oversee the entire ML lifecycle. **Responsibilities:** - Design and implement technical features using best practices for the relevant technology stack - Collaborate with client-facing teams to grasp the solution context, contribute to technical requirement gathering and analysis - Work alongside technical architects to validate design and implementation strategies - Write production-ready code that is easily testable, comprehensible to other developers, and addresses edge cases and errors - Ensure top-notch quality deliverables by adhering to architecture/design guidelines, coding best practices, and engaging in periodic design/code reviews - Develop unit tests and higher-level tests to handle expected edge cases, errors, and optimal scenarios - Utilize bug tracking, code review, version control, and other tools for organizing and delivering work - Participate in scrum calls, agile ceremonies, and effectively communicate progress, issues, and dependencies - Contribute consistently by researching and evaluating the latest technologies, conducting proofs-of-concept, and creating prototype solutions - Aid the project architect in designing modules/components of the overall project/product architecture - Break down large features into estimable tasks, lead estimation, and defend them with clients - Independently implement complex features with minimal guidance, such as service or application-wide changes - Systematically troubleshoot code issues/bugs using stack traces, logs, monitoring tools, and other resources - Conduct code/script reviews of senior engineers within the team - Mentor and cultivate technical talent within the team **Requirements:** - Minimum 5+ years of hands-on experience in deploying and productionizing ML models at scale - Proficiency in scaling GenAI or similar applications to accommodate high user traffic, large datasets, and reduce response time - Strong expertise in developing RAG-based pipelines using frameworks like LangChain & LlamaIndex - Experience in crafting GenAI applications such as answering engines, extraction components, and content authoring - Expertise in designing, configuring, and utilizing ML Engineering platforms like Sagemaker, MLFlow, Kubeflow, or other relevant platforms - Familiarity with Big data technologies including Hive, Spark, Hadoop, and queuing systems like Apache Kafka/Rabbit MQ/AWS Kinesis - Ability to quickly adapt to new technologies, innovate in solution creation, and independently conduct POCs on emerging technologies - Proficiency in at least one Programming language such as PySpark, Python, Java, Scala, etc., and solid foundations in Data Structures - Hands-on experience in building metadata-driven, reusable design patterns for data pipeline, orchestration, and ingestion patterns (batch, real-time) - Experience in designing and implementing solutions on distributed computing and cloud services platforms (e.g., AWS, Azure, GCP) - Hands-on experience in constructing CI/CD pipelines and awareness of application monitoring practices **Additional Skills:** - AWS/Azure Solutions Architect certification with a comprehensive understanding of the broader AWS/Azure stack - Knowledge of DevOps CI/CD, data security, and experience in designing on cloud platforms - Willingness to travel to global offices as required to collaborate with clients or internal project teams **Perks & Benefits:** ZS provides a holistic total rewards package encompassing health and well-being, financial planning, annual leave, personal growth, and professional development. The organization offers robust skills development programs, various career progression options, internal mobility paths, and a collaborative culture that empowers individuals to thrive both independently and as part of a global team. ZS is committed to fostering a flexible and connected work environment that enables employees to combine work from home and on-site presence at clients/ZS offices for the majority of the week. This approach allows for the seamless integration of the ZS culture and innovative practices through planned and spontaneous face-to-face interactions. **Travel:** Travel is an essential aspect of working at ZS, especially for client-facing roles. Business needs dictate the priority for travel, and while some projects may be local, all client-facing employees should be prepared to travel as required. Travel opportunities provide avenues to strengthen client relationships, gain diverse experiences, and enhance professional growth through exposure to different environments and cultures. **Application Process:** Candidates must either possess or be able to obtain work authorization for their intended country of employment. To be considered, applicants must submit an online application, including a complete set of transcripts (official or unofficial). *Note: NO AGENCY CALLS, PLEASE.* For more information, visit [ZS Website](www.zs.com).,

Techvantage.ai is a next-generation technology and product engineering company at the forefront of innovation in Generative AI, Agentic AI, and autonomous intelligent systems. We create intelligent, user-first digital products that redefine industries through the power of AI and engineering excellence. We are looking for a Senior Software Engineer-AI with 4-6 years of hands-on experience in Artificial Intelligence/ML and a passion for innovation. This role is ideal for someone who thrives in a startup environment, fast-paced, product-driven, and full of opportunities to make a real impact. You will contribute to building intelligent, scalable, and production-grade AI systems, with a strong focus on Generative AI and Agentic AI technologies. As a Senior Software Engineer-AI at Techvantage.ai, you will be responsible for building and deploying AI-driven applications and services, focusing on Generative AI and Large Language Models (LLMs). You will design and implement Agentic AI systemsautonomous agents capable of planning and executing multi-step tasks. Collaborate with cross-functional teams including product, design, and engineering to integrate AI capabilities into products. Write clean, scalable code and build robust APIs and services to support AI model deployment. Own feature delivery end-to-endfrom research and experimentation to deployment and monitoring. Stay current with emerging AI frameworks, tools, and best practices and apply them in product development. Contribute to a high-performing team culture and mentor junior team members as needed. In order to excel in this role, we are seeking candidates with 3-6 years of overall software development experience, with at least 3 years specifically in AI/ML engineering. Strong proficiency in Python is required, along with hands-on experience in PyTorch, TensorFlow, and Transformers (Hugging Face). Proven experience working with LLMs (e.g., GPT, Claude, Mistral) and Generative AI models (text, image, or audio) is highly desirable. Practical knowledge of Agentic AI frameworks (e.g., LangChain, AutoGPT, Semantic Kernel) is a plus. Experience building and deploying ML models to production environments is essential. Familiarity with vector databases (Pinecone, Weaviate, FAISS) and prompt engineering concepts is beneficial. Comfortable working in a startup-like environment is crucialself-motivated, adaptable, and willing to take ownership. A solid understanding of API development, version control, and modern DevOps/MLOps practices is expected from the ideal candidate.,

As the Senior Director, Artificial Intelligence (AI) at Quorum Software, you will play a crucial role in establishing and leading the AI Innovation Center. Your primary focus will be on designing, developing, and deploying cutting-edge AI solutions across our software portfolio, with a vision to accelerate our AI strategy by utilizing technologies such as machine learning, generative AI, agentic AI, and advanced analytics to create transformative products and capabilities for the energy sector. Your responsibilities will include leading the AI Innovation Center to drive research and development in AI and ML technologies specific to energy-related software use cases. You will define and execute the company's AI strategy, including identifying suitable platforms, tools, and applied AI models. Collaborating with cross-functional teams, you will develop AI-driven product features, services, and decision-support tools across our software ecosystem. Your role will also involve overseeing the development and deployment of ML models, agentic systems, and generative AI applications to enhance customer experience and drive positive business outcomes. Furthermore, you will be instrumental in building and leading a high-performing AI & Data Science team, fostering a culture of innovation, experimentation, and impact. It will be your responsibility to ensure the responsible and ethical use of AI, complying with industry standards and regulatory requirements, especially those relevant to the energy industry. Staying abreast of the latest advancements in the field, you will evaluate and select AI/ML tools, frameworks, and platforms. Additionally, you will represent the company in industry forums, conferences, and AI research communities to promote innovation and thought leadership. To excel in this role, you should hold a Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related technical field, with a preference for a Master's degree. With over 10 years of experience in AI/ML, including at least 5 years in a leadership capacity, you should have a proven track record of successfully applying AI, machine learning, and generative/agentic AI in commercial software products. Strong communication skills, stakeholder management abilities, and experience presenting to executive leadership are essential for this position. Moreover, familiarity with energy industry data types, standards, and use cases, as well as knowledge of MLOps, data governance, and responsible AI practices, would be advantageous. While visa sponsorship is not provided for this position, applicants requiring reasonable accommodations during the application or interview process should contact the Human Resources Department.,

About Agoda Agoda is an online travel booking platform that provides accommodations, flights, and more. The company utilizes cutting-edge technology to connect travelers with a global network of 4.7M hotels and holiday properties worldwide, along with flights, activities, and additional services. As part of Booking Holdings and based in Asia, Agoda's team of 7,100+ employees from 95+ nationalities across 27 markets fosters a work environment that thrives on diversity, creativity, and collaboration. The company prioritizes innovation through a culture of experimentation and ownership to enhance the customer experience and enable people to explore the world. Purpose: Bridging the World Through Travel Agoda believes that travel enriches people's lives by providing opportunities to enjoy, learn, and experience the wonders of the world. Travel brings individuals and cultures closer together, fostering empathy, understanding, and happiness. Team Overview: The Data department at Agoda is responsible for managing all data-related requirements. The primary objective is to enhance the use of data within the company by implementing various resources such as operational and analytical databases, queue systems, BI tools, and data science technology. The Data team comprises talented individuals from around the world who are equipped with the necessary knowledge and tools to drive personal growth and success while upholding Agoda's culture of diversity and experimentation. The team's role is pivotal as it supports business users, product managers, engineers, and other stakeholders in making informed decisions and improving the overall customer experience. The Opportunity: As an ML Technical Product Manager at Agoda, you will play a crucial role in empowering employees with the tools needed to make informed decisions and develop innovative features for end users. Your responsibilities will include defining internal product requirements, analyzing data, generating ideas, designing features, managing projects, providing training, and ensuring the quality of solutions. You will collaborate with various teams to conceptualize platform capabilities that enhance external customer experiences and contribute to Agoda's journey as a data-driven company. In This Role, You'll Get to: - Take ownership of the product lifecycle from concept to implementation and analysis. - Gather and synthesize requirements from multiple stakeholders to drive product development. - Engage with internal customers to understand user needs, priorities, and feature considerations. - Demonstrate strong leadership, organizational skills, and the ability to drive projects in a fast-paced environment. - Communicate effectively across all levels of the organization to align teams and influence decision-making. - Bridge the gap between business and technical aspects to deliver optimal solutions. What You'll Need To Succeed: - 5+ years of technical experience in ML engineering, Data Science, or related fields. - 2+ years of technical program/product management experience in a fast-paced setting. - Excellent interpersonal, presentation, and organizational skills. - Strong communication skills to engage with both business and technical teams effectively. - Analytical mindset with the ability to use data for decision-making. - Familiarity with product management tools like JIRA. - Problem-solving skills and a positive attitude towards challenges. - Willingness to relocate to Bangkok, Thailand, with relocation support provided. Equal Opportunity Employer Note: Agoda does not accept third-party resumes and is not responsible for any fees related to unsolicited resumes. Your application will be kept on file for future opportunities, and you can request to have your details removed as per our privacy policy.,

Job Overview The Applied AI Solutions Architect is a strategic role responsible for designing, implementing, and managing AI-driven solutions that align with business objectives. This position bridges technical expertise in artificial intelligence (AI) and machine learning (ML) with business strategy, ensuring scalable, ethical, and high-performing AI systems. The AI Solutions Architect collaborates with cross-functional teams to deliver innovative solutions, leveraging generative AI, cloud platforms, and modern architectures like Retrieval-Augmented Generation (RAG). Responsibilities Solution Design : Architect end-to-end AI/ML pipelines, including data ingestion, preprocessing, model training, deployment, and monitoring, ensuring scalability and performance. Technology Selection : Evaluate and select appropriate AI frameworks, tools, and cloud services (e.g., AWS SageMaker, Azure AI, Google Cloud AI) based on project requirements. Generative AI Implementation : Design solutions using large language models (LLMs) and RAG architectures for applications like content generation, customer engagement, or product design. Collaboration : Work with data scientists, engineers, product managers, and executives to translate business needs into technical solutions, acting as a trusted advisor. Governance and Ethics : Implement responsible AI practices, addressing bias, security, and compliance in AI systems. MLOps and AIOps : Establish CI/CD pipelines, model versioning, and monitoring frameworks to operationalize AI solutions. Thought Leadership : Advocate for AI-driven innovation, mentor teams, and communicate technical concepts to non-technical stakeholders. Performance Optimization : Ensure AI solutions meet latency, cost, and quality requirements, optimizing for production environments. Skill Set Technical Skills : Proficiency in Python, R, or Julia for AI/ML development. Expertise in ML frameworks like TensorFlow, PyTorch, Hugging Face, or Scikit-learn. Experience with cloud platforms (AWS, Azure, Google Cloud) and AI services like Amazon Bedrock or Azure AI Foundry. Knowledge of MLOps tools (e.g., Kubeflow, MLflow) and CI/CD pipelines. Familiarity with generative AI techniques, including prompt engineering, fine-tuning, and RAG. Understanding of data engineering concepts, including ETL processes and data lakes. Soft Skills : Strong communication to bridge technical and business teams. Analytical thinking for evaluating trade-offs and designing optimal solutions. Leadership and mentorship to guide cross-functional teams. Domain Knowledge : Experience in industries like healthcare, finance, or technology, with an understanding of relevant use cases (e.g., drug discovery, personalized marketing). Certifications AWS Certified Machine Learning Specialty Microsoft Azure AI Engineer Associate Google Cloud Professional Machine Learning Engineer Coursera or Edureka AI/ML certifications (e.g., DeepLearning.AIs Generative AI Specialization) ITIL or TOGAF for enterprise architecture alignment (optional) Qualifications Bachelors or Masters degree in Computer Science, Data Science, or a related field. 8+ years of experience in ML engineering, data science, or software architecture, with 3+ years in AI/ML solution design. Proven track record of deploying AI solutions in production environments

Brief About Fractal Fractal Analytics is Leading Fortune 500 companies leverage Big Data, analytics and technology to drive smarter, faster and more accurate decisions in every aspect of their business. Fortune 500 companies recognize analytics is a competitive advantage to understand s and make better decisions. We deliver insight, innovation and impact to them through predictive analytics and visual storytelling. Role & Responsibilities: Experience of working on end-to-end data science pipeline with the ability to clearly design efficient data models, training data samples, training pipelines and inference pipelines to ensure reproducibility. Strong experience in evaluating different types of AI/ML outputs and models (recommender systems, similarity scoring, classification and regression). Should be able to break down complex business problems into sub-tasks that can be solved with AI/ML to enable decision making at scale. Should have good grasp on statistical concepts and empirical methods that drive post-modeling decisions like sorting, ranking , selection etc. Should have good experience in converting PoCs and experimented models into production grade AIML systems , have the ability to collaborate effectively with ML engineering and MLOPs teams to take AI/ML models to production, build and serve models through APIs and support integration of AI/ML models into web-aps. Ability to lead mid-sized teams, plan project tracks around AI/ML and data science and balance delegation and hands-on development. Experience in taking first principles approach to solving data science problems, understand and communicate data requirements to data engineering teams and explain model outputs to business users. Ability and experience in engaging business users to understand requirements and translate them into technical data science problems. Be exceptional at communicating and translating model algorithms and their outputs to non-technical users and stakeholders. Fluent in agile ways of working and agile project management practices. Should be comfortable to create efficient user stories, and other agile project artifacts.

Key Responsibilities: LLM Deployment & Optimization Deploy, fine-tune, and optimize open-source LLMs (e.g., LLaMA, Mistral, CodeS, DeepSeek). Implement quantization (e.g., 4-bit, 8-bit) and pruning for efficient inference on commodity hardware. Build and manage inference APIs (REST/gRPC) for production use. Infrastructure Management Set up and manage on-premise GPU servers and VM-based deployments. Build scalable cloud-based LLM infrastructure using AWS (SageMaker, EC2), Azure ML, or GCP Vertex AI. Ensure cost efficiency by choosing appropriate hardware and job scheduling strategies. MLOps & Reliability Engineering Develop CI/CD pipelines for model training, testing, evaluation, and deployment. Integrate version control for models, data, and hyperparameters. Set up logging, tracing, and monitoring tools (e.g., MLflow, Prometheus, Grafana) for model performance and failure detection. Security, Compliance & Performance Ensure data privacy (FERPA/GDPR) and enforce security best practices across deployments. Apply secure coding standards and implement RBAC, encryption, and network hardening for cloud/on-prem. Cross-functional Integration Work closely with AI solution engineers, backend developers, and product owners to integrate LLM services into the platform. Support performance benchmarking and A/B testing of AI features across modules. Documentation & Internal Enablement Document LLM pipelines, configuration steps, and infrastructure setup in internal playbooks. Create guides and reusable templates for future deployments and models. Key Requirements: Education: Bachelors or Masters in Computer Science, AI/ML, Data Engineering, or related field. Technical Skills: Strong Python experience with ML libraries (e.g., PyTorch, Hugging Face Transformers). Familiar with LangChain, LlamaIndex, or other RAG frameworks. Experience with Docker, Kubernetes, and API gateways (e.g., Kong, NGINX). Working knowledge of vector databases (FAISS, Pinecone, Qdrant). Familiarity with GPU deployment tools (CUDA, Triton Inference Server, HuggingFace Accelerate). Experience: 4+ years in an AI/MLOps role, including experience in LLM fine-tuning and deployment. Hands-on work with model inference in production environments (both cloud and on-prem). Exposure to SaaS and modular product environments is a plus.

Agoda is an online travel booking platform that connects travelers with a vast network of 4.7M hotels and holiday properties worldwide, in addition to flights, activities, and more. As part of Booking Holdings and based in Asia, Agoda comprises a diverse team of 7,100+ employees from 95+ nationalities across 27 markets. The work environment at Agoda is characterized by diversity, creativity, and collaboration, fostering a culture of experimentation and ownership to enhance the customer experience. The primary goal of Agoda is to bridge the world through travel, believing that travel enables people to enjoy, learn, and experience the world, bringing individuals and cultures closer together. The team at Agoda is skilled, driven, and diverse, united by a passion to make a positive impact. Leveraging innovative technologies and strong partnerships, Agoda aims to make travel easy and rewarding for everyone. The Data department at Agoda is responsible for overseeing all data-related requirements within the company. The department's ultimate objective is to enable and enhance the use of data through creative approaches and the implementation of powerful resources such as operational and analytical databases, queue systems, BI tools, and data science technology. The Data team at Agoda plays a critical role in empowering decision-making processes for various stakeholders across the organization, including business users, product managers, and engineers. Additionally, the team is dedicated to improving the search experience for customers and safeguarding them from fraudulent activities. As an ML Technical Product Manager at Agoda, you will play a key role in empowering employees with the tools necessary to make informed decisions and develop advanced features and models for users by leveraging collected data. Your responsibilities will include managing internal product requirements, analyzing data, ideating features, designing roadmaps, project management, providing trainings, and ensuring the quality of solutions. You will work towards conceptualizing platform capabilities that empower the organization to create exceptional external customer experiences, contributing to Agoda's status as a data-driven company. In this role, you will have the opportunity to own the product lifecycle from concept to design, implementation, and analysis. You will gather and synthesize requirements from various stakeholders, lead discussions with internal customers, demonstrate strong leadership and organizational skills, and collaborate effectively with both business and technical teams. The successful candidate will possess 5+ years of technical experience in ML engineering, Data Science, or related roles, along with 2+ years of technical program/product management experience in a fast-paced environment. Strong communication skills, organizational abilities, and a problem-solving mindset are essential for this role. This position requires the successful candidate to relocate fully to Bangkok, Thailand, where relocation support will be provided. Agoda is an equal opportunity employer, and applications will be kept on file for future vacancies. For more information, please refer to our privacy policy. Agoda does not accept third-party resumes, and recruitment agencies are advised not to send resumes to Agoda employees or any other organization location. Agoda is not responsible for any fees related to unsolicited resumes.,

What You'll Do We are seeking an experienced and experienced AI & Machine Learning Technical Manager to lead our dynamic team in developing cutting-edge AI & ML solutions. This role is perfect for someone passionate about applying AI and ML, promote innovation, and create impactful products. You will be responsible for our AI systems (conversational agents, tax code classification for products and services, document intelligence, etc.) and how we apply them at Avalara to simplify and scale tax compliance across our entire portfolio of products. As an important part of our leadership team, you will shape the future of our AI & ML projects, manage a talented team of AI professionals, and collaborate with teams to implement projects. We offer the chance to work on pioneering AI technologies and mentor a team of experts, and contribute to the strategic direction of our AI & ML endeavors. This role will report to Sr Director of AI & ML. What Your Responsibilities Will Be Lead and manage a team of AI&ML engineers and data scientists, overseeing project lifecycles from conception to deployment, ensuring timely delivery. Develop team members, providing guidance on technical challenges, career development, and professional growth opportunities. Stay up to date with the latest AI&ML technologies and methodologies, incorporating new approaches into our projects to maintain competitive advantage. Develop our AI&ML strategy, aligning with our objectives, and ensuring the team's projects support this vision. Collaborate with teams, including product management, engineering, and design, to define project requirements, set priorities, and allocate resources effectively. Foster a culture of innovation, encouraging experimentation and learning, and leading by example in adopting a hands-on approach to problem-solving. Ensure implementing best practices in project management, software development, and quality assurance to optimize team performance and productivity. Manage stakeholder communications, providing regular updates on project status, important milestones, and any challenges or risks, ensuring alignment and support across the organization. What You'll Need to be Successful Specific Qualifications: Expertise in AI technologies and methodologies, with a portfolio of projects demonstrating your ability to apply these in solving complex problems. Experience building and deploying to production APIs powered by AI & Machine Learning systems. Proficiency in programming languages relevant to AI & ML, such as Python, R, Java, Scala, C++ and familiarity with AI & ML frameworks and libraries (e.g., PyTorch, TensorFlow, and Scikit-learn). Experience with cloud computing platforms (AWS, Azure, Google Cloud) and understanding of how to use these for scalable, secure, reliable distributed systems with complex workflows relying on AI & ML solutions. Background in data engineering and familiarity with database technologies, as well as, data processing / ETL pipelines and visualization tools. General Qualifications: Bachelor's degree in Computer Science, Artificial Intelligence, or Machine Learning. 9 years of experience in AI & ML with at least 6 years in a management position, overseeing technical teams. Translate complex technical concepts and challenges into clear strategic plans and applicable solutions. People management skills, with experience mentoring and developing teams. Excellent project management skills, with experience in agile methodologies

Entity :- Accenture Strategy & Consulting Team :- Global Network Data & AI Practice :- AI Managed Services Title: - AI LLM Technology Architecture Consultant Role :- ML Engineering Consultant Job Location:- Hyderabad Accenture Global Network - Data & AI practice help our clients grow their business in entirely new ways.Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition As part of our Data & AI practice, you will join a worldwide network of smart and driven colleagues experienced in leading AI/ML/Statistical tools, methods and applications. From data to analytics and insights to actions, our forward-thinking consultants provide analytically-informed, issue-based insights at scale to help our clients improve outcomes and achieve high performance. WHATS IN IT FOR YOU An opportunity to work on high-visibility projects with top clients around the globe. Potential to Co-create with leaders in strategy, industry experts, enterprise function practitioners, and business intelligence professionals to shape and recommend innovative solutions that leverage emerging technologies. Ability to embed responsible business into everythingfrom how you service your clients to how you operate as a responsible professional. Personalized training modules to develop your strategy & consulting acumen to grow your skills, industry knowledge, and capabilities. Opportunity to thrive in a culture that is committed to accelerating equality for all. Engage in boundaryless collaboration across the entire organization. What you would do in this role Hands on experience on ML Services of AWS or Azure or Google. Develop, train, and deploy machine learning models for real-world applications. Design and implement data pipelines for model training and inference. Conduct model evaluation, testing, and validation to ensure robustness and accuracy. Work with large-scale datasets to build and improve predictive models. Optimize and fine-tune ML algorithms for performance, scalability, and efficiency. Collaborate with data scientists, software engineers, and product teams to integrate ML solutions into production systems. Stay up-to-date with the latest trends and advancements in machine learning and AI. Write clean, maintainable, and well-documented code. Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law. Qualification Who are we looking for Bachelors or Masters degree in any engineering stream or MCA. Experience/Education on Statistics, Data Science, Applied Mathematics, Business Analytics, Computer Science, Information Systems is preferable. Proven experience (5+ years) in working as per the above job description is required. Exposure to Retail, Banking, Healthcare projects is added advantage. Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. Strong understanding of algorithms, statistical modeling, and data structures. Experience with cloud platforms (AWS, GCP, Azure) and ML deployment tools (Docker, Kubernetes, MLflow, etc.). Knowledge of SQL and NoSQL databases for data handling. Familiarity with MLOps best practices for continuous integration and deployment of ML models. Excellent problem-solving skills and ability to work in a collaborative team environment. Ability to solve complex business problems and deliver client delight. Strong writing skills to build points of view on current industry trends. Good Client handling skills; able to demonstrate thought leadership & problem-solving skills.

We are seeking a skilled AI/ML Engineer to develop and integrate advanced deep learning solutions into our medical imaging platform. You will work on high-impact use cases such as analyzing MRI scans to assist in Alzheimer's prediction and diagnosis, ensuring your models meet clinical accuracy and performance standards. Key Responsibilities: Develop and fine-tune deep learning models (CNNs, ANNs, Transformers) for medical image classification, segmentation, and anomaly detection. Handle medical imaging data formats (e.g., DICOM, NIfTI) for preprocessing and feature extraction. Integrate trained AI models into existing medical imaging platforms using industry-standard deployment pipelines. Collaborate with radiologists, data scientists, and software engineers to validate model performance and usability. Implement model monitoring and update strategies post-deployment to ensure reliability and compliance. Document methodologies, model architecture decisions, and deployment workflows. Required Skills & Qualifications: 4+ years of experience in AI/ML , with at least 2 years focused on medical or biomedical image processing . Strong hands-on experience with deep learning frameworks : TensorFlow , PyTorch , Keras . Proficient in Python , with good working knowledge of SQL for data management. Experience working with medical imaging libraries and toolkits such as MONAI , OpenCV , SimpleITK , and scikit-image . Familiarity with cloud-based AI deployment tools and services on AWS , GCP , or Azure . Solid understanding of image annotation , model evaluation metrics (e.g., Dice coefficient, ROC-AUC) , and regulatory implications in healthcare AI. Preferred Skills (Nice to Have): Experience with federated learning, explainable AI (XAI), or multimodal learning in healthcare. Exposure to containerization (Docker) and MLOps practices for scalable AI deployments. Familiarity with PACS systems , FHIR , or integration with HL7 standards . Knowledge of FDA/CE regulatory requirements for AI in medical devices.

We are seeking a skilled AI/ML Engineer to develop and integrate advanced deep learning solutions into our medical imaging platform. You will work on high-impact use cases such as analyzing MRI scans to assist in Alzheimer's prediction and diagnosis, ensuring your models meet clinical accuracy and performance standards. Key Responsibilities: Develop and fine-tune deep learning models (CNNs, ANNs, Transformers) for medical image classification, segmentation, and anomaly detection. Handle medical imaging data formats (e.g., DICOM, NIfTI) for preprocessing and feature extraction. Integrate trained AI models into existing medical imaging platforms using industry-standard deployment pipelines. Collaborate with radiologists, data scientists, and software engineers to validate model performance and usability. Implement model monitoring and update strategies post-deployment to ensure reliability and compliance. Document methodologies, model architecture decisions, and deployment workflows. Required Skills & Qualifications: 4+ years of experience in AI/ML , with at least 2 years focused on medical or biomedical image processing . Strong hands-on experience with deep learning frameworks : TensorFlow , PyTorch , Keras . Proficient in Python , with good working knowledge of SQL for data management. Experience working with medical imaging libraries and toolkits such as MONAI , OpenCV , SimpleITK , and scikit-image . Familiarity with cloud-based AI deployment tools and services on AWS , GCP , or Azure . Solid understanding of image annotation , model evaluation metrics (e.g., Dice coefficient, ROC-AUC) , and regulatory implications in healthcare AI. Preferred Skills (Nice to Have): Experience with federated learning, explainable AI (XAI), or multimodal learning in healthcare. Exposure to containerization (Docker) and MLOps practices for scalable AI deployments. Familiarity with PACS systems , FHIR , or integration with HL7 standards . Knowledge of FDA/CE regulatory requirements for AI in medical devices.

What You'll Do We are seeking an experienced Senior AI & Machine Learning Manager to lead our dynamic team in developing cutting-edge AI & ML solutions. This role is perfect for someone passionate about leveraging AI and ML, inspire creativity, and create impactful products. You will be responsible for our Generative AI systems and how we apply them at Avalara to simplify and scale tax compliance across our entire portfolio of products. Major initiatives currently involve creating conversational agents. As an integral part of our leadership team, you will have the opportunity to shape the future of our AI & ML initiatives, manage a talented team of AI professionals, and collaborate with cross-functional teams to implement strategic projects. This role will report to Sr Director of AI & ML. What Your Responsibilities Will Be Lead and manage a team of AI&ML engineers, overseeing project lifecycles from conception to deployment, ensuring high-quality standards and timely delivery. Mentor and develop team members, providing guidance on technical challenges, career development, and professional growth opportunities. Stay abreast of the latest AI&ML technologies and methodologies, incorporating new and innovative approaches into our projects to maintain competitive advantage. Develop and execute our AI&ML strategy, aligning with the company's objectives, and ensuring the team's projects support this vision. Collaborate with cross-functional teams, including product management, engineering, and design, to define project requirements, set priorities, and allocate resources effectively. Ensure operational excellence, implementing best practices in project management, software development, and quality assurance to optimize team performance and productivity. Manage stakeholder communications, providing regular updates on project status, key milestones, and any challenges or risks, ensuring alignment and support across the organization. What You'll Need to be Successful Specific Qualifications: Proven expertise in Gen AI technologies and methodologies, with a strong portfolio of projects demonstrating your ability to apply these in solving complex problems. Experience with building and deploying to enterprise production environments APIs powered by AI & Machine Learning systems. Proficiency in programming languages relevant to AI & ML, such as Python, R, Java, Scala, C++ and familiarity with AI & ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with cloud computing platforms (AWS, Azure, Google Cloud) and understanding of how to leverage these for scalable, secure, reliable distributed systems with complex workflows relying on AI & ML solutions. Strong background in data engineering and familiarity with database technologies, as well as, data processing ETL pipelines and visualization tools. General Qualifications: Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related science field. A minimum of 10 years of experience in AI & ML with at least 5 years in a leadership or management position, overseeing technical teams. Excellent project management skills, with experience in agile methodologies.

Role & responsibilities 3+ years of experience in Spark, Databricks, Hadoop, Data and ML Engineering. 3+ Years on experience in designing architectures using AWS cloud services & Databricks. Architecture, design and build Big Data Platform (Data Lake / Data Warehouse / Lake house) using Databricks services and integrating with wider AWS cloud services. Knowledge & experience in infrastructure as code and CI/CD pipeline to build and deploy data platform tech stack and solution. Hands-on spark experience in supporting and developing Data Engineering (ETL/ELT) and Machine learning (ML) solutions using Python, Spark, Scala or R languages. Distributed system fundamentals and optimising Spark distributed computing. Experience in setting up batch and streams data pipeline using Databricks DLT, jobs and streams. Understand the concepts and principles of data modelling, Database, tables and can produce, maintain, and update relevant data models across multiple subject areas. Design, build and test medium to complex or large-scale data pipelines (ETL/ELT) based on feeds from multiple systems using a range of different storage technologies and/or access methods, implement data quality validation and to create repeatable and reusable pipelines Experience in designing metadata repositories, understanding range of metadata tools and technologies to implement metadata repositories and working with metadata. Understand the concepts of build automation, implementing automation pipelines to build, test and deploy changes to higher environments. Define and execute test cases, scripts and understand the role of testing and how it works. Preferred candidate profile Big Data technologies Databricks, Spark, Hadoop, EMR or Hortonworks. Solid hands-on experience in programming languages Python, Spark, SQL, Spark SQL, Spark Streaming, Hive and Presto Experience in different Databricks components and API like notebooks, jobs, DLT, interactive and jobs cluster, SQL warehouse, policies, secrets, dbfs, Hive Metastore, Glue Metastore, Unity Catalog and ML Flow. Knowledge and experience in AWS Lambda, VPC, S3, EC2, API Gateway, IAM users, roles & policies, Cognito, Application Load Balancer, Glue, Redshift, Spectrum, Athena and Kinesis. Experience in using source control tools like git, bit bucket or AWS code commit and automation tools like Jenkins, AWS Code build and Code deploy. Hands-on experience in terraform and Databricks API to automate infrastructure stack. Experience in implementing CI/CD pipeline and ML Ops pipeline using Git, Git actions or Jenkins. Experience in delivering project artifacts like design documents, test cases, traceability matrix and low-level design documents. Build references architectures, how-tos, and demo applications for customers. Ready to complete certifications

Responsibilities Contribute to the industrialization of the ML & GenAI technical stacks of our AI Platform, by participating in their definition, architecture, development, test, documentation & maintenance phases. Ensure the development process of this stack follows the DevSecOps recommendations & best practices . Write ML pipelines to illustrate the AI Platform capabilities. Contribute to the CI/CD workflows developments to automate the integration and deployment of the various ML assets (code or models) into the different environments. Contribute to the definition of the LLMOps / MLOps operating model and make sure the AI Platform enforces this model. Collaborate with our internal stakeholders to co-design the new features of the AI Platform . Occasionally be embarked into one of our stakeholder teams to help them using the AI platform, write ML pipelines, and, in return, collect platform evolution needs. Occasionally contribute to the collective effort of run & support for the AI Platform. Qualifications Requirements and Skills 5+ years of experience in ML Engineering. Strong knowledge on Machine Learning (including ML model management context) and GenAI technologies (including RAG). Previous hands-on experience on MLOps or LLMOps disciplines is mandatory . Good knowledge of DevOps processes at scale and experience of production systems. Rigorous mindset (but still open to changes), oriented towards customers, problems solving & results. Good team player . Autonomous . Ideally, some knowledge of Energy Management and Automation market . At ease in an international work environment & fluent in English . Familiar with agile methodologies: Scrum, SAFe. Technologies: Azure and/or AWS cloud technologies and their respective ML platforms (AzureML, AWS SageMaker). Databricks. GitHub, Terraform. ML Tools such as MLFlow. GenAI & LLM tools

Role Overview We are seeking a skilled and innovative Machine Learning Engineer with expertise in Large Language Models (LLMs) to join our team. The ideal candidate has hands-on experience developing, fine-tuning, and deploying LLMs, alongside a deep understanding of the machine learning lifecycle. This role involves building scalable AI solutions, collaborating with cross-functional teams, and contributing to cutting-edge AI initiatives. Key Responsibilities Model Development & Optimization: Develop, fine-tune, and deploy LLMs like OpenAI's GPT, Anthropic's Claude, Googles Gemini, or AWS Bedrock. Customize pre-trained models for specific use cases, ensuring high performance and scalability. Machine Learning Pipeline Design: Build and maintain end-to-end ML pipelines, from data preprocessing to model deployment. Optimize training workflows for efficiency and accuracy. Integration & Deployment: Work closely with software engineering teams to integrate ML solutions into production environments. Ensure APIs and solutions are scalable and robust. Experimentation & Research: Experiment with new architectures, frameworks, and approaches to improve model performance. Stay updated with advancements in LLMs and generative AI technologies. Collaboration: Collaborate with cross-functional teams, including data scientists, engineers, and product managers, to align ML solutions with business goals. Provide mentorship to junior team members as needed. Required Qualifications Experience: At least 5 years of professional experience in machine learning or AI development. Proven experience with LLMs and generative AI technologies. Technical Skills: Proficiency in Python (required) and basic knowledge of Java is needed Hands-on experience with APIs and tools like OpenAI, Anthropic's Claude, Google Gemini, or AWS Bedrock. Familiarity with ML frameworks such as TensorFlow, PyTorch, or Hugging Face. Strong understanding of data structures, algorithms, and distributed systems. Cloud Expertise: Experience with AWS, GCP, or Azure, including services relevant to ML workloads (e.g., AWS SageMaker, Bedrock). Data Engineering: Proficiency in handling large-scale datasets and implementing data pipelines. Experience with ETL tools and platforms for efficient data preprocessing. Problem Solving: Strong analytical and problem-solving skills, with the ability to debug and resolve issues quickly. Preferred Qualifications Experience with multi-modal models and generative AI for images, text, or other modalities. Understanding of ML Ops principles and tools (e.g., MLflow, Kubeflow). Familiarity with reinforcement learning and its applications in AI. Knowledge of distributed training techniques and tools like Horovod or Ray. Advanced degree (Masters or Ph.D.) in Computer Science, Machine Learning, or a related field.

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