146 Ml Ops Jobs - Page 2

About the Role We are seeking a Machine Learning Ops Engineer to support and scale our ML/AI infrastructure. The role involves working with LangServe, LangFuse, Docker, and Kubernetes to deploy, monitor, and optimize ML models in production environments. Key Responsibilities • Assist in designing and managing ML model deployment pipelines . • Work with LangServe to deploy and serve ML/LLM applications. • Implement monitoring and logging using LangFuse for model performance tracking. • Containerize ML applications with Docker and deploy them on Kubernetes clusters . • Collaborate with Data Scientists to integrate ML models into production systems. • Support CI/CD pipelines for model updates and versioning. • Ensure system reliability, scalability, and automation for ML workloads. Required Skills • 24 years of experience in ML Ops • Hands-on experience with LangServe and LangFuse . • Good understanding of Docker (building images, managing containers). • Exposure to Kubernetes (deployment, scaling, Helm, monitoring). • Programming skills in Python (preferred) or Java . • Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn). • Understanding of CI/CD tools (GitHub Actions, Jenkins, etc.). • Basic knowledge of cloud platforms (AWS / GCP / Azure). Good to Have • Exposure to LangChain or RAG pipelines . • Knowledge of observability tools ( Prometheus, Grafana, ELK ). • Understanding of ML lifecycle management (MLflow, DVC). Educational Qualification • Bachelors degree in Computer Science, Data Science, AI/ML, or related field.

As a Lead Data Scientist specializing in Natural Language Processing (NLP) and Computer Vision (OpenCV), you will play a crucial role in driving our AI initiatives. Your primary responsibilities will include designing, developing, and deploying cutting-edge NLP and computer vision models to address real-world challenges across various data domains such as text, image, and structured data. Your expertise will be instrumental in setting the technical direction, guiding junior team members, and enhancing our data science capabilities organization-wide. A key aspect of your role will involve hands-on leadership in research and development using advanced ML/DL techniques. You will lead by example in mentoring junior and mid-level data scientists, contributing to their professional growth. Collaboration with cross-functional teams, including Engineering, Product, and Business units, will be essential as you drive high-impact AI projects and shape the strategic roadmap for data science within the company. Your proficiency in applying advanced NLP techniques with tools like spaCy, HuggingFace Transformers, BERT, and GPT will be critical in delivering successful outcomes. Additionally, your experience in solving computer vision challenges using OpenCV, PyTorch, and TensorFlow will be invaluable in driving innovation and performance tuning initiatives. Working with cloud platforms such as Azure and AWS for model training, deployment, and monitoring will also be part of your regular tasks. To excel in this role, you should possess at least 6 years of hands-on experience in data science, with a specific focus on NLP and computer vision for at least 4 years. Strong Python skills, familiarity with ML fundamentals, and experience in deploying ML models in cloud environments are prerequisites. Your ability to communicate effectively in English, both verbally and in writing, will be essential for engaging with technical and non-technical stakeholders across different geographies. In this role, you will have the opportunity to be part of a mission-driven company that values innovation, autonomy, and collaboration. With a clear path to grow into a Head of Data Science position, you can lead meaningful AI projects and contribute directly to the success of the organization. The role offers a flexible remote work environment with monthly in-person collaboration in Indore and occasional international travel, providing a dynamic and forward-thinking work experience where your contributions make a tangible impact on company growth.,

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate Job Description & Summary At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes forour 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 foreach 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 firms 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. Responsibilities: 4+ 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: ML Ops, AI / ML Preferred skill sets: ML Ops, AI / ML Years of experience required: 4 - 8 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 Degree, Bachelor Degree Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills Product Management Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Algorithm Development, Alteryx (Automation Platform), Analytical Thinking, Analytic Research, Big Data, Business Data Analytics, Communication, Complex Data Analysis, Conducting Research, Creativity, Customer Analysis, Customer Needs Analysis, Dashboard Creation, Data Analysis, Data Analysis Software, Data Collection, Data-Driven Insights, Data Integration, Data Integrity, Data Mining, Data Modeling, Data Pipeline + 38 more 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

As a member of the Pega Product Management India team, you will focus on Pega Decision Management and Analytics. You will work closely with our Engineering teams and Technical Services Operations (TSO) teams to drive and deliver the market-differentiating Decision Management capabilities in our Products. Pega Product Management team drives the Product vision and strategy with an innovation mindset to deliver a low-code platform for AI-powered decisioning and workflow automation. As the Product Manager for Decision Management, Predictive and Adaptive Analytics, you will define the roadmap and vision for Decision Management, Predictive Analytics, Marketing in the Pega Products. You will be ensuring your ideas are designed and delivered by collaborating with Engineering teams and Designer teams. You will be charged with defining the cohesive, market-differentiating capabilities in Pega's next generation products for the critical areas of Decision Management. Key attributes of successful product outcomes will include an emphasis on real-world sophistication in getting customer adoption with capabilities that are effective, efficient, secured, prescriptive experience, seamless upgrades, and operational excellence. Maintain a product backlog of top priority Decision Management and Predictive Analytics related enhancements. Lead the definition, prioritization, and coordinated delivery of market-leading capabilities across design, engineering, and release management teams. Iterative and incremental delivery of working software on a month-to-month basis, adopted and fully aligned with the broader vision and roadmap for the Pega Platform. Work closely with the architects to ensure your offering is architected in accordance with best practice and operable with our standard Pega Cloud offerings. Demonstrate engaged enterprise thought leadership; you are not afraid to step up and take accountability for clarifying uncertainty, ambiguity, and support removing obstacles in support of delivering market-leading software. Create competitive analysis and regularly measure progress against our competitors. Regularly update the delivery roadmap (3 months out) and full year quarterly roadmap based on competitive analysis and a clear understanding of our internal and external client and partner needs. Collaborate with other teams and groups to deliver high-quality software with minimal tech debt in accordance with our software development life cycle (SDLC). Meet with clients and analysts to showcase innovations. Pursue patents, and work with the legal team to submit patent ideas. 6-10 years of experience working in a product organization, focusing on ideating, designing, and delivering capabilities. Strong affinity with predictive analytics, statistics, ML ops and monitoring. Exposure with coding / awareness of concepts in R, Python (highly desired). Understand core machine learning concepts, algorithms, and workflows. Experience with Machine Learning platforms and frameworks. Strong communication skills with experience in building impactful content including presentations, interactive product demos, webinars, videos, and case studies. Experience collaborating and engaging with sales teams, customers, prospects, analysts, and internal management. Ability to work effectively across silos to drive understanding, buy-in, and prioritization. Strong analytical skills, an attention to detail, and an overall can-do attitude. Pega Offers You: - Gartner Analyst acclaimed technology leadership across our categories of products - Continuous learning and development opportunities - An innovative, inclusive, agile, flexible, and fun work environment,

Job Description Oracle Cloud Infrastructure team is continuing our fast-paced growth, bringing on new customers around the world daily. Our Customer Operations team is responsible for making sure our customers receive prompt & informative answers that quickly solve any question or issue they have encountered. At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world. Values are OCIs foundation and how we deliver excellence. We strive for equity, inclusion, and respect for all. We are committed to the greater good in our products and our actions. We are constantly learning and taking opportunities to grow our careers and ourselves. We challenge each other to stretch beyond our past to build our future. You are the builder here. You will be part of a team of really smart, motivated, and diverse people and given the autonomy and support to do your best work. It is a dynamic and flexible workplace where youll belong and be encouraged. We are looking for a Sr. Software Developer Engineer and team lead with a passion for data and analytics to join the TOS ML/AI Platform team. The team provides accurate data and partners with teams to help them discover actionable narratives, both by describing the past and predicting the future. We believe information enables success, and we are committed to providing clear insights for all levels of the organization. The ideal candidate will possess the technical ability to identify and break down challenging technical problems in an agile, fluid environment, as well as design and implement NLP and other LLM/Gen AI solutions to those problems . They will be results-driven and excited to use their expertise to help create an engineering environment that embodies the best development and testing practices for delivering a high-quality service. The purpose of a Senior ML Engineer is to partner with data scientists to gain insights into data by architecting and implementing data-driven solutions. If you are passionate about taking ownership of big technical challenges and producing software solutions that have broad, significant impacts - come join our team! Responsibilities In this role, you will: Design, build, and manage a ML platform environment to support data science programs/initiatives in a cloud environment Study and transform data science prototypes and build ML Pipelines & LLM frameworks Work with highly unstructured textual data and derive insights using NLP techniques Assist with the design, prototype, test, and implementation of descriptive, predictive, sentiment, clustering, and translation models Collaborate with data scientists, and stewards during design discussions to uncover more detailed business requirements related to data science programs/initiatives Be a champion for CI/CD and development best practices, especially around automation and testing Collaborate across roles to embrace best practices in reporting and analysis, including data integrity, test design, validation, and documentation Be an technical leader to a team of engineers focused on platform design, architecture, availability, and features Deploy & Maintain ML (LLM/NLP) models in production and establish processes for ML Ops Perform statistical analysis and fine-tuning using test results Train and retrain systems based on model performance Extend existing ML libraries and frameworks Mandatory Qualifications: Bachelor&aposs or Masters degree in Computer Science or related technical field or equivalent professional experience Ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy Proven experience as a Machine Learning Engineer or similar role using NLP and LLMs Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala Understanding of data structures, infrastructure, distributed computing principles, data modeling and software architecture Experience in building scalable end-to-end data platform solutions supporting data science Experience with leading edge LLM frameworks like RAG, ReAct and Outage Detection Able to independently operate in an ambiguous and fast paced environment Deep knowledge of math, probability, statistics and algorithms Experience with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn) Strong software development and deployment skills Preferred Qualifications: 5+ years of experience as a ML/software development engineer 3+ years of experience developing cloud software services and an understanding of design for security, scalability, performance, and reliability Preferred Experience with NLP, primarily focused around clustering, topic modeling, recommendation systems etc. Hands on experience working on large-scale data science/data analytics projects and building large-scale machine learning infrastructure to support them Experience defining system architectures and exploring technical feasibility trade-offs A successful history of manipulating, processing and extracting value from large disconnected datasets Confidently taking responsibility for the technical output of a project Ability to quickly pick up new skills and learn on the job Comfortably working with various stakeholders such as TPMs, data scientists, architects and other developers Experience with Oracle Cloud Infrastructure technology stack or equivalent cloud experience Experience with ML toolkits and ML Ops Experience mentoring software development engineers Qualifications Career Level - IC3 About Us As a world leader in cloud solutions, Oracle uses tomorrows technology to tackle todays challenges. Weve partnered with industry-leaders in almost every sectorand continue to thrive after 40+ years of change by operating with integrity. We know that true innovation starts when everyone is empowered to contribute. Thats why were committed to growing an inclusive workforce that promotes opportunities for all. Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. Were committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing [HIDDEN TEXT] or by calling +1 888 404 2494 in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law. Show more Show less

Inviting applications for the role of Assistant Manager, ML Ops Engineer! We are seeking a highly skilled and experienced ML Ops / LLM Ops Engineer to join our team. You will play a crucial role in building and maintaining the infrastructure and pipelines for our cutting-edge Generative AI applications, working closely with the Generative AI Full Stack Architect. Your expertise in automating and streamlining the ML lifecycle will be instrumental in ensuring the efficiency, scalability, and reliability of our Generative AI models in production. Responsibilities Design, develop, and implement ML/LLM pipelines for generative AI models, encompassing data ingestion, pre-processing, training, deployment, and monitoring. MLOps Support and Maintenance on ML Platforms Dataiku/ Sagemaker Apply understanding of Dataiku Govern functionalities, including item and artifact management, workflow control, and sign-off processes. Using best practices for data governance and model accountability within the MLOps lifecycle. Automate ML tasks across the model lifecycle, leveraging tools like GitOps , CI/CD pipelines, and containerization technologies (e.g., Docker, Kubernetes). Implement version control, CI/CD pipelines, and containerization techniques to streamline ML and LLM workflows. Design and implement monitoring and alerting systems to track model performance, data drift, and other key metrics. Conduct ground truth analysis to evaluate the accuracy and effectiveness of LLM outputs compared to known, correct data. Work closely with infrastructure and DevOps teams to provision and manage resources for ML and LLM development and deployment. Develop and maintain robust monitoring and alerting systems for generative AI models in production, ensuring proactive identification and resolution of issues. Collaborate with the Generative AI Full Stack Architect and other engineers to optimize model performance and resource utilization. Manage and maintain cloud infrastructure (e.g., AWS, Azure) for ML workloads, ensuring cost-efficiency and scalability. Stay up to date on the latest advancements in MLOps and incorporate them into our platform and processes. Communicate effectively with technical and non-technical stakeholders about the health and performance of generative AI models. Qualifications we seek in you! Minimum Qualifications Bachelor's degree in computer science, Data Science, Engineering, or a related field, or equivalent experience. Experience in MLOps or related areas, such as DevOps, data engineering, or ML infrastructure. Knowledge of best practices for data governance and model accountability within the MLOps lifecycle. Covered these Dataiku Certifications: ML Practitioner Certificate, Advanced Designer Certificate and MLOps Practitioner Certificate. Proven experience in ML Ops, LLM Ops, or related roles, with hands-on experience deploying and managing machine learning and large language model pipelines Expertise in cloud platforms (e.g., AWS, Azure) for ML workloads. Strong understanding of CI/CD principles and containerization technologies like Docker and Kubernetes. Familiarity with monitoring and alerting tools for ML systems (e.g., Prometheus, Grafana). Excellent communication, collaboration, and problem-solving skills. Ability to work independently and as part of a team. Passion for Generative AI and its potential to revolutionize various industries.

Exciting opportunity for an ML Platform Specialist to join a leading technology-driven firm. You will be designing, deploying, and maintaining scalable machine learning infrastructure with a strong focus on Databricks, model lifecycle, and MLOps practices. Location: Gurugram (Hybrid) Your Future Employer Our client is a leading digital transformation partner driving innovation across industries. With a strong focus on data-driven solutions and cutting-edge technologies, they are committed to fostering a collaborative and growth-focused environment. Responsibilities Designing and implementing scalable ML infrastructure on Databricks Lakehouse Building CI/CD pipelines and workflows for machine learning lifecycle Managing model monitoring, versioning, and registry using MLflow and Databricks Collaborating with cross-functional teams to optimize machine learning workflows Driving continuous improvement in MLOps and automation strategies Requirements Bachelors or Masters in Computer Science, ML, Data Engineering, or related field 3-5 years of experience in MLOps , with strong expertise in Databricks and Azure ML Proficient in Python, PySpark, MLflow, Delta Lake, and Databricks Feature Store Hands-on experience with cloud platforms ( Azure/AWS/GCP ), CI/CD, Git Knowledge of Terraform, Kubernetes, Azure DevOps , and distributed computing is a plus Whats in it for you Competitive compensation with performance-driven growth opportunities Work on cutting-edge MLOps infrastructure and enterprise-scale ML solutions Collaborative, diverse, and innovation-driven work culture Continuous learning, upskilling, and career development support

As a Machine Learning Engineer, your primary responsibility will be to develop, train, and validate predictive and analytical models using machine learning techniques. You will collaborate closely with data engineers and business teams to define data requirements and success metrics. In addition, you will deploy machine learning models into production following ML Ops best practices and build automated pipelines for model training, testing, monitoring, and retraining. Your role will also involve optimizing model performance, ensuring scalability and reliability, monitoring model drift and performance degradation, and continuously improving the models. Furthermore, you will implement CI/CD practices for machine learning workflows. To excel in this role, you must possess a strong proficiency in Python, including libraries such as Pandas, NumPy, Scikit-learn, and PyTorch/TensorFlow. Experience with ML Ops tools/frameworks like MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, or Azure ML is essential. A good understanding of data engineering concepts such as ETL, data pipelines, and APIs is required, along with hands-on experience in containerization and orchestration using Docker and Kubernetes. Knowledge of cloud platforms like AWS, GCP, or Azure for ML model deployment is also crucial. Your background should include a strong foundation in statistics, machine learning algorithms, and model evaluation techniques, along with familiarity with version control using Git and CI/CD pipelines. Ideally, you should hold a Bachelors or Masters degree in Computer Science, Data Science, Statistics, or a related field. Previous experience in handling large-scale data pipelines and real-time model serving will be advantageous. Exposure to feature stores and automated model monitoring is a plus. Strong problem-solving, analytical, and communication skills are highly desirable for this role.,

About this role: Wells Fargo is seeking a Senior Software Engineer. In this role, you will: Lead moderately complex initiatives and deliverables within technical domain environments Contribute to large scale planning of strategies Design, code, test, debug, and document for projects and programs associated with technology domain, including upgrades and deployments Review moderately complex technical challenges that require an in-depth evaluation of technologies and procedures Resolve moderately complex issues and lead a team to meet existing client needs or potential new clients needs while leveraging solid understanding of the function, policies, procedures, or compliance requirements Collaborate and consult with peers, colleagues, and mid-level managers to resolve technical challenges and achieve goals Lead projects and act as an escalation point, provide guidance and direction to less experienced staff Required Qualifications: 4+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Strong Python programming skills Expertise in RPA tools such as UI path Expertise in Workflow automation tools such as Power Platform Minimum 2 Years of hands-on experience in AI/ML and Gen AI Proven experience in LLMs (Gemini, GPT or Llama etc.) Extensive experience in Prompt Engineering and model fine tuning AI/Gen AI Certifications from premier institution Hands on experience in ML ops (MLflow, CICD pipelines) Job Expectations: Design and develop AI driven Automation solutions Implement AI automation to enhance process automation Develop and maintain automation, BOTS and AI based workflows Integrate Ai automation with existing applications, APIs and databases Design, develop and implement Gen AI applications using LLMs Build and optimize prompt engineering workflows Fine tune and integrate pre-trained models for specific use cases Deploy models in production using robust MLops practices

Profile Description Were seeking someone to join our team as AI Platform Engineering Specialist who will have strong hands-on experience building software platforms on any combination of the following platforms - Kubernetes, Cloud (AWS, Azure, and/or Google), API based development, REST framework, data engineering, and large-scale API Gateway environments etc. Knowledge of AIML and hands-on experience implementing solutions using Generative AI are also preferable. The candidate will have great communication skills, a team-based mentality and a strong passion for using AI to increase productivity as well as help generate new ideas for product & technical improvements. Enterprise_Technology Enterprise Technology & Services (ETS) delivers shared technology services for Morgan Stanley supporting all business applications and end users. ETS provides capabilities for all stages of Morgan Stanleys software development lifecycle, enabling productive coding, functional and integration testing, application releases, and ongoing monitoring and support for over 3,000 production applications. ETS also delivers all workplace technologies (desktop, mobile, voice, video, productivity, intranet/internet) in integrated configurations that boost the personal productivity of employees. Application and end user functions are delivered on a scalable, secure, and reliable infrastructure composed of seamlessly integrated datacenter, network, compute, cloud, storage, and database functions. Architecture & Modernization Architecture & Modernization Drives development of the global firm strategy to define modern architectures and guardrails to reduce legacy debt, while partnering with app dev to accelerate the adoption of modern capabilities. Software Engineering This is a position that develops and maintains software solutions that support business needs. Morgan Stanley is an industry leader in financial services, known for mobilizing capital to help governments, corporations, institutions, and individuals around the world achieve their financial goals. At Morgan Stanley India, we support the Firms global businesses, with critical presence across Institutional Securities, Wealth Management, and Investment management, as well as in the Firms infrastructure functions of Technology, Operations, Finance, Risk Management, Legal and Corporate & Enterprise Services. Morgan Stanley has been rooted in India since 1993, with campuses in both Mumbai and Bengaluru. We empower our multi-faceted and talented teams to advance their careers and make a global impact on the business. For those who show passion and grit in their work, theres ample opportunity to move across the businesses for those who show passion and grit in their work. Interested in joining a team thats eager to create, innovate and make an impact on the world Read on What Youll Do In The Role Develop tooling and self-service capabilities for deploying AI solutions for the firm leveraging Kubernetes/OpenShift, Python, authentication solutions, APIs, REST framework, etc. Develop Terraform modules and Cloud architecture to enable secure AI cloud service deployment and consumption at scale. Have a platform mindset and build common, reusable solutions to scale Generative AI use cases using pre-trained models as well as fine-tuned models. Leverage Kubernetes/OpenShift to develop modern containerized workloads. Integrate with capabilities such as large-scale vector stores for embeddings. Author best practices on the Generative AI ecosystem, when to use which tools, available models such as GPT, Llama, Hugging Face etc. and libraries such as Langchain. Analyze, investigate, and implement GenAI solutions focusing on Agentic Orchestration and Agent Builder frameworks. Author and publish architecture decision records to capture major design decisions and product selection for building Generative AI solutions. Inclusive of app authentication, service communication, state externalization, container layering strategy and immutability. Ensure AI platform are reliable, scalable, and operational; (e.g. blueprints for upgrade/release strategies (E.g. Blue/Green); logging/monitoring/metrics; automation of system management tasks) Participate in all teams Agile/ Scrum ceremonies. Participate in teams on call rotation in build/run team model What Youll Bring To The Role At least 4 years relevant experience would generally be expected to find the skills required for this role Bachelors or Masters degree in Computer Science or related field, or equivalent job experience 4 years of experience in software engineering, design and development Strong hands-on Application Development background in at least one prominent programming language, preferably Python Flask or FAST Api. Broad understanding of data engineering (SQL, NoSQL, Big Data, Kafka, Redis), data governance, data privacy and security. Experience in development, management, and deployment of Kubernetes workloads, preferably on OpenShift. Experience with designing, developing, and managing RESTful services for large-scale enterprise solutions. Experience deploying applications on Azure, AWS, and/or GCP using IaC (Terraform) Hands-on experience with multiprocessing, multithreading, asynchronous I/O, performance profiling in at least one prominent programming language, preferably python. Ability to articulate technical concepts effectively to diverse audiences. Excellent communication skills. Demonstrated ability to work effectively and collaboratively in a global organization, across time zones, and across organizations Demonstrated experience in DevOps, understanding of CI/CD (Jenkins) and GitOps. Knowledge of DevOps and Agile practices. Nice to have Practitioner of unit testing, performance testing and BDD/acceptance testing. Understanding of OAuth 2.0 protocol for secure authorization. Proficiency with Open Telemetry tools including Grafana, Loki, Prometheus, and Cortex. Good knowledge of Microservice based architecture, industry standards, for both public and private cloud. Good understanding of modern Application configuration techniques. Hands on experience with Cloud Application Deployment patterns like Blue/Green. Good understanding of State sharing between scalable cloud components (Kafka, dynamic distributed caching). Good knowledge of various DB engines (SQL, Redis, Kafka, etc) for cloud app storage. Experience building AI applications, preferably Generative AI and LLM based apps. Deep understanding of AI agents, Agentic Orchestration, Multi-Agent Workflow Automation, along with hands-on experience in Agent Builder frameworks such Lang Chain and Lang Graph. Experience working with Generative AI development, embeddings, fine tuning of Generative AI models. Understanding of ModelOps/ ML Ops/ LLM Op. Understanding of SRE techniques. What You Can Expect From Morgan Stanley We are committed to maintaining the first-class service and high standard of excellence that have defined Morgan Stanley for over 89 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - arent just beliefs, they guide the decisions we make every day to do what&aposs best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, youll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. Theres also ample opportunity to move about the business for those who show passion and grit in their work. To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser. Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential. Our skilled and creative workforce is comprised of individuals drawn from a broad cross section of the global communities in which we operate and who reflect a variety of backgrounds, talents, perspectives, and experiences. Our strong commitment to a culture of inclusion is evident through our constant focus on recruiting, developing, and advancing individuals based on their skills and talents. Show more Show less

Technical Skillset : Must Have Skills - Generative AI - GPT3, ML Ops and Python Proficient in Python, with experience in machine learning, deep learning, and NLP processing. Experience in developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs. Proficient in Langchain, LLM Prompt Engineering : The engineer prompts and optimizes few-shot techniques to enhance LLM's performance on specific tasks, e.g. personalized recommendations. Model Evaluation & Optimization : Evaluate LLM's zero-shot and few-shot capabilities, fine-tuning hyperparameters, ensuring task generalization, and exploring model interpretability for robust web app integration. Response Quality : Collaborate with ML and Integration engineers to leverage LLM's pre-trained potential, delivering contextually appropriate responses in a user-friendly web app. It is essential to have a solid understanding of data structures, algorithms, and principles of software engineering. Experience with vector databases RDBMS, MongoDB and NoSQL databases. Proficiency in working with embeddings. Strong distributed systems skills and system architecture skills Experienced in building and running a large platform at scale. Hands-on experience with Python, Hugging Face, TensorFlow, Keras, PyTorch, Spark, or similar statistical tools. Experience as data modeling ML/NLP scientist. including, but not limited to, Performance tuning, fine-tuning, RLHF, and performance optimization. Validated background with ML toolkits, such as PyTorch, TensorFlow, Keras, Langchain, Llamadindex, SparkML, or Databricks. Proficient with the integration of data from multiple data sources Experience with NoSQL databases, such as HBase, ElasticSearch, and MongoDB API Design. API/Data mapping to schema. Experienced in and strong knowledge of using AI/ML and more particularly LLMs eager to apply this rapidly changing technology. Good Knowledge of Kubernetes, and RESTful design. Prior experience in developing public cloud services or open-source ML software is an advantage Role and responsibilities - Collaborating with cross-functional teams to define AI project requirements and objectives ensuring alignment with overall business goals Conducting research to stay up to date with the latest advancements in generative AI machine learning and deep learning techniques and identify opportunities to integrate them into our products and services. Optimizing existing generative AI models for improved performance scalability and efficiency. Active participation in developer communities, open-source contributions, or personal GenAI projects Work closely with the GenAI development team to integrate AI models and applications with the existing/new tool, quality, and performance. Act as an authority, guiding junior engineers and collaborating teams, fostering a culture of development excellence, collaboration, and continuous learning. Evaluating and selecting appropriate AI tools and machine learning models for tasks, as well as building and training working versions of those models using Python and other open-source technologies Working with leadership and stakeholders to identify AI opportunities and promote strategy. Serve as a technical lead, overseeing and supervising projects and engineers on the team. Play a leading hands-on role in the design and implementation of our ML infrastructure and GenAI platform software technologies. Drive our technology vision and roadmap. Establish software development best practices, and lead by example in applying them Experience contributing to the architecture and design of large scale distributed systems and/or ML systems and tools Hands-on experience leveraging large sets of structured and unstructured data to develop data-driven tactical and strategic analytics and insights using ML, NLP, computer vision solutions Strong sense of software design and usability of ML systems Experience applying software engineering methodologies and best practices including coding standards, code reviews, build processes, testing, and security. Proven experience as a Engineering Lead, hands on Software Engineering Manager, or similar role Develop natural language processing (NLP) solutions using GenAI, LLMs and custom transformer architectures. Adopt and customize LLM agent-based orchestration tools (LlamaIndex, Langchain, Semantic Kernel) for enterprise applications and use cases Implement information search and retrieval at scale, using a range of solutions ranging from keyword search to semantic search using embeddings. Developing and/or tune Large Language Models (LLM) and Generative AI (GAI) Analyze, design, develop, support and maintain Big Data environment and code base, support traditional data pipelines and processes. Education Computer science, Data Engineering, or a related field graduates.

Req ID: 328025 NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now. We are currently seeking a Systems Integration Specialist to join our team in Bangalore, Karntaka (IN-KA), India (IN). Experience: 4-6 years Key Responsibilities: . Build machine learning models to predict asset health, process anomalies, and optimize operations. . Work on sensor data pre-processing, model training, and inference deployment. . Collaborate with simulation engineers for closed-loop systems. Skills Required: . Experience in time-series modeling, regression/classification, and anomaly detection. . Familiarity with Python, scikit-learn, TensorFlow/PyTorch. . Experience with ML Ops on Azure ML, Databricks, or similar. . Understanding of manufacturing KPIs (e.g., OEE, MTBF, cycle time). About NTT DATA NTT DATA is a $30 billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long term success. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity. We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a part of NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Visit us at NTT DATA endeavors to make accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at . This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click . If you'd like more information on your EEO rights under the law, please click . For Pay Transparency information, please click.

Total - 12+years 7-11 years(AIML), 3+ yrs exp in solution Architect (Hands on project exp) 1-2yrs project exp in Gen AI Positions: AIML Solution Architect Location: Chennai/Hyderabad Experience Range: 12-18yrs Role Summary: The AI Solutioning Architect leads the technical solutioning and architecture of AI-driven projects within the organization, from initial conception through to successful deployment. This role is responsible for ensuring that all AI solutions are strategically aligned with business goals, technically sound, and operationally efficient. This individual will work closely with cross-functional teams to design and implement innovative AI solutions that address complex healthcare challenges within the Healthcare IT landscape. The AI Solutioning Architect plays a critical role in defining the AI/ML strategy and ensuring its successful implementation across the organization. Essential Responsibilities: Lead the technical solutioning process for all AI-related projects, ensuring alignment with business objectives, architectural standards, and the overall AI/ML strategy. Define and maintain the architectural vision and roadmap for AI solutions, incorporating best practices, emerging technologies, and the evolving needs of the Healthcare IT domain. Design end-to-end AI solutions, including data ingestion, processing, model development, deployment, and monitoring, with a focus on scalability, reliability, and security. Work closely with business stakeholders to understand requirements and translate them into technical specifications, while also contributing to the overall strategic direction of AI initiatives. Collaborate with data scientists, engineers, and other technical experts to ensure successful project execution, providing technical guidance and mentorship throughout the development lifecycle. Develop and maintain comprehensive documentation of AI solutions, including architecture diagrams, design specifications, and implementation guidelines, to facilitate knowledge sharing and collaboration. Evaluate and recommend AI technologies, platforms, and tools to support the organization's AI initiatives, with a focus on leveraging Google Cloud Platform (GCP) services where appropriate. Provide technical guidance and mentorship to project teams, fostering a culture of innovation, excellence, and continuous improvement. Lead proof-of-concept (POC) projects to validate the feasibility and value of proposed AI solutions, ensuring that they align with the organization's strategic goals. Ensure that AI solutions are scalable, secure, and compliant with relevant regulations and standards, including HIPAA and other Healthcare IT requirements. Stay abreast of the latest trends and advancements in AI and related fields, and proactively identify opportunities for innovation and competitive advantage. Work with US and Thryve leaders to provide project status, risk assessment, and strategic recommendations, ensuring that stakeholders are informed and aligned on project goals and timelines. Effectively communicate complex technical concepts to both technical and non-technical audiences, fostering collaboration and alignment across the organization. Required Skills and Qualifications: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field. 12+ years of experience in software development or architecture, with a significant focus on AI and machine learning. Deep understanding of AI/ML concepts and techniques, including supervised, unsupervised, and reinforcement learning, as well as experience with various AI algorithms and models. Hands-on experience with cloud computing platforms (e.g., AWS, Azure, GCP), with a strong preference for experience with Google Cloud Platform (GCP) and its AI-related services. Proven experience in designing and implementing scalable and robust AI solutions within the Healthcare IT domain. Strong programming skills in languages such as Python, Java, or Scala, as well as experience with AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. Excellent communication, presentation, and interpersonal skills, with the ability to effectively communicate complex technical concepts to diverse audiences. Proven ability to lead technical discussions and influence decision-making, with a demonstrated track record of successfully driving AI initiatives within an organization. Experience in working with cross-functional teams and stakeholders, with a strong ability to collaborate and build consensus. Strong analytical and problem-solving skills, with a demonstrated ability to identify and address complex technical challenges. Knowledge of healthcare industry standards and regulations (e.g., HIPAA) is required, as well as a strong understanding of the Healthcare IT landscape. Experience with MLOps practices and tools, with a focus on automating and streamlining the AI development and deployment lifecycle. Strong leadership skills, with the ability to provide technical guidance and mentorship to project teams.

One of the Healthcare AI Product Start up based out of Hyderabad is looking out for a AI Architect. If you are looking for a challenging environment and would like to be a part of building AI products, let us connect and discuss. Position: AI Architect Experience: 5+ yrs Qualification: B.Tech / B.E from Tier 1 Academic Institutions Job Type: Permanent & WFO Job Location: Hyderabad Position Overview We are seeking an experienced AI Architect to lead the design, development, and deployment of large-scale AI solutions. The ideal candidate will bridge the gap between business requirements and technical implementation, with deep expertise in generative AI and modern MLOps practices. Key Responsibilities: AI Solution Design & Implementation: • Architect end-to-end AI systems leveraging large language models and generative AI technologies • Design scalable, production-ready AI applications that meet business objectives and performance requirements • Evaluate and integrate LLM APIs from leading providers (OpenAI, Anthropic Claude, Google Gemini, etc.) • Establish best practices for prompt engineering, model selection, and AI system optimization Model Development & Fine-tuning: • Fine-tune open-source models (Llama, Mistral, etc.) for specific business use cases • Implement custom training pipelines and evaluation frameworks • Optimize model performance, latency, and cost for production environments • Stay current with latest model architectures and fine-tuning techniques Infrastructure & Deployment: • Deploy and manage AI models at enterprise scale using containerization (Docker) and orchestration (Kubernetes) • Build robust, scalable APIs using FastAPI and similar frameworks • Design and implement MLOps pipelines for model versioning, monitoring, and continuous deployment • Ensure high availability, security, and performance of AI systems in production Business & Technical Leadership: • Collaborate with stakeholders to understand business problems and translate them into technical requirements • Provide technical guidance and mentorship to development teams • Conduct feasibility assessments and technical due diligence for AI initiatives • Create technical documentation, architectural diagrams, and implementation roadmaps Required Qualifications: Experience • 5+ years of experience in machine learning engineering or data science • 1+ years of hands-on experience building, deploying, and managing generative AI models in production • Proven track record of delivering large-scale ML solutions Technical Skills: • Expert-level proficiency with LLM APIs (OpenAI, Claude, Gemini, etc.) • Hands-on experience fine-tuning transformer models (Llama, Mistral, etc.) • Strong proficiency in FastAPI, Docker, and Kubernetes • Experience with ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers) • Proficiency in Python and modern software development practices • Experience with cloud platforms (AWS, GCP, or Azure) and their AI/ML services Core Competencies: • Strong understanding of transformer architectures, attention mechanisms, and modern NLP techniques • Experience with MLOps tools and practices (model versioning, monitoring, CI/CD) • Ability to translate complex business requirements into technical solutions • Strong problem-solving skills and architectural thinking Preferred Qualifications: • Experience with vector databases and retrieval-augmented generation (RAG) systems • Knowledge of distributed training and model parallelization techniques • Experience with model quantization and optimization for edge deployment • Familiarity with AI safety, alignment, and responsible AI practices • Experience in specific domains (finance, healthcare, legal, etc.) • Advanced degree in Computer Science, AI/ML, or related field Please Note: We are looking out for candidates who shorter notice period.

Qualcomm India Private Limited is a leading technology innovator that drives digital transformation to enable next-generation experiences and create a smarter, connected future for all. As a Qualcomm Software Engineer, your role involves designing, developing, modifying, and validating embedded and cloud edge software, applications, and specialized utility programs to launch cutting-edge products that exceed customer needs. You will collaborate with various teams to design system-level software solutions and obtain information on performance requirements and interfaces. Minimum Qualifications: - Bachelor's degree in Engineering, Information Systems, Computer Science, or related field with 3+ years of Software Engineering experience - OR Master's degree in relevant field with 2+ years of experience - OR PhD in relevant field with 1+ year of experience - 2+ years of academic or work experience with Programming Languages such as C, C++, Java, Python, etc. - Location: Hyderabad - Experience: 1-5 Years We are looking for experienced Machine Learning Engineers with expertise in Generative AI to join our core AI team. The ideal candidate will focus on designing, developing, and deploying cutting-edge generative AI solutions, specifically in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Intelligent agent systems. Key Responsibilities: - Design and implement RAG-based solutions to enhance LLM capabilities with external knowledge sources - Develop and optimize LLM fine-tuning strategies for specific use cases and domain adaptation - Create robust evaluation frameworks to measure and improve model performance - Build and maintain agentic workflows for autonomous AI systems - Collaborate with cross-functional teams to identify opportunities and implement AI solutions Required Qualifications: - Bachelor's or Master's degree in Computer Science or related field - 3+ years of experience in Machine Learning/AI engineering - Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow) - Practical experience with LLM deployments and fine-tuning - Experience with vector databases and embedding models - Familiarity with modern AI/ML infrastructure and cloud platforms (AWS, GCP, Azure) - Strong understanding of RAG architectures and implementation Preferred Qualifications: - Experience with popular LLM frameworks (Langchain, LlamaIndex, Transformers) - Knowledge of prompt engineering and chain-of-thought techniques - Experience with containerization and microservices architecture - Background in NLP and deep learning - Background in Reinforcement Learning - Contributions to open-source AI projects - Experience with ML ops and model deployment pipelines Skills and Competencies: - Strong problem-solving and analytical skills - Excellent communication and collaboration abilities - Experience with agile development methodologies - Ability to balance multiple projects and priorities - Strong focus on code quality and best practices - Understanding of AI ethics and responsible AI development Qualcomm is an equal opportunity employer committed to providing accessible processes for individuals with disabilities. Accommodations can be requested by emailing disability-accommodations@qualcomm.com or calling Qualcomm's toll-free number. Qualcomm expects its employees to adhere to all applicable policies and procedures, including security and confidentiality requirements. Note: The provided email address is solely for requesting accommodations for individuals with disabilities. Requests for updates on applications or resume inquiries will not be addressed here. Staffing and recruiting agencies are not authorized to use the Qualcomm Careers Site for submissions. Unsolicited resumes or applications will not be accepted. For more information, please contact Qualcomm Careers.,

Aera Technology is the Decision Intelligence company. Our platform, Aera Decision Cloud, integrates with enterprise systems to digitize, augment, and automate decisions in real time. We deliver millions of AI-powered recommendations each year, generating significant value for some of the world's largest brands. We are seeking a Machine Learning Engineer (Support & Ops focus) to ensure our AI-powered decision systems run reliably at scale. This role is less about building models from scratch, and more about keeping production AI systems healthy, observable, and performant, while enabling Data Science teams to deliver faster. This position is also a strong career pathway into ML feature development - you will work closely with Product, Data Science, and Engineering teams, gain exposure to LLMs, Agentic AI, and advanced ML tooling, and progressively take on more responsibilities in building new ML-powered product features. Responsibilities: - Monitor, troubleshoot, and maintain ML pipelines and services in production, ensuring high availability and minimal downtime. - Work closely with Data Scientists and Engineers to operationalize ML/LLM models, from development through deployment. - Build and maintain observability tools for tracking data quality, model performance, drift detection, and inference metrics. - Support LLM and Agentic AI features in production, focusing on stability, optimization, and seamless integration into the platform. - Develop and enhance internal ML tooling for faster experimentation, deployment, and feature integration. - Collaborate with Product teams to roll out new ML-driven features and improve existing ones. - Work with DevOps to improve CI/CD workflows for ML code, data pipelines, and models. - Optimize resource usage and costs for large-scale model hosting and inference. - Document workflows, troubleshooting guides, and best practices for ML systems support. About You: - B.E./B.Tech in Computer Science, Engineering, or related field. - 3-5 years of experience in software engineering, ML Ops, or ML platform support. - Strong Python skills, with experience in production-grade code and automation. - Experience with ML pipeline orchestration tools (Airflow, Prefect, Kubeflow, or similar). - Familiarity with containerized microservices (Docker, Kubernetes) and CI/CD pipelines. - Experience monitoring ML systems using tools like Prometheus, Grafana, ELK, Sentry, or equivalent. - Understanding of model packaging and serving frameworks (FastAPI, TorchServe, Triton Inference Server, Hugging Face Inference API). - Strong collaboration skills with cross-functional teams. Good to Have: - Exposure to LLM operations (prompt engineering, fine-tuning, inference optimization). - Familiarity with Agentic AI workflows and multi-step orchestration (LangChain, LlamaIndex). - Experience with data versioning (DVC, Delta Lake) and experiment tracking (MLflow, Weights & Biases). - Knowledge of vector databases (Pinecone, Weaviate, FAISS). - Experience with streaming data (Kafka) and caching (Redis). - Skills in cost optimization for GPU workloads. - Basic understanding of system design for large-scale AI infrastructure. If you share our passion for building a sustainable, intelligent, and efficient world, you're in the right place. Established in 2017 and headquartered in Mountain View, California, we're a series D start-up, with teams in Mountain View, San Francisco (California), Bucharest and Cluj-Napoca (Romania), Paris (France), Munich (Germany), London (UK), Pune (India), and Sydney (Australia). So join us, and let's build this! Benefits Summary: At Aera Technology, we strive to support our Aeranauts and their loved ones through different stages of life with a variety of attractive benefits and great perks. In addition to offering a competitive salary and company stock options, we have other great benefits available. You'll find comprehensive medical, Group Medical Insurance, Term Insurance, Accidental Insurance, paid time off, Maternity leave, and much more. We offer unlimited access to online professional courses for both professional and personal development, coupled with people manager development programs. We believe in a flexible working environment, to allow our Aeranauts to perform at their best, ensuring a healthy work-life balance. When you're working from the office, you'll also have access to a fully-stocked kitchen with a selection of snacks and beverages.,

As a S&C GN AI - Insurance AI Generalist Consultant at Accenture, you will play a key role in driving strategic initiatives, managing business transformations, and leveraging industry expertise to create value-driven solutions. Your responsibilities will include providing strategic advisory services, conducting market research, and developing data-driven recommendations to enhance business performance. You will have the opportunity to work with Accenture's Global Network, a unified powerhouse that combines the capabilities of Strategy & Consulting with Data and Artificial Intelligence. This role will involve architecting, designing, building, deploying, delivering, and monitoring advanced analytics models, including GenAI, to solve client problems. You will also be responsible for developing functional aspects of Generative AI pipelines and interfacing with clients to understand engineering and business problems. The ideal candidate for this role will have at least 5 years of experience in data-driven techniques, including exploratory data analysis, data pre-processing, machine learning, and visualization. A Bachelor's or Master's degree in Mathematics, Statistics, Economics, Computer Science, or a related field is required. Strong analytical, problem-solving, and communication skills are essential, along with proficiency in programming languages such as Python, PySpark, SQL, and Scala. Experience in implementing AI solutions for the Insurance industry and production-grade integration of AI/ML pipelines is preferred. Additionally, familiarity with Azure, AWS, or Databricks tools, as well as GenAI, LLMs, RAG architecture, and Lang chain frameworks, would be beneficial. Strong communication, collaboration, and presentation skills are necessary to effectively convey complex data insights and recommendations to clients and stakeholders. Joining Accenture offers you the opportunity to work on innovative projects, experience career growth, and gain leadership exposure. If you thrive in a fast-paced, dynamic environment and are passionate about leveraging Generative AI to drive business success, this role is perfect for you.,

Enhancor is a customer service firm specializing in outsourced accounting, regulatory compliance, information technology, and financial services for real estate and property management companies based in the U.S. With offices in New York and Pune, Enhancor provides 24/7, around-the-clock resources to its clients. The Enhancor team has experience interfacing with some of the largest property managers in the world, providing services to multi-family operators, including those with more than $7 billion in real estate assets. We are looking for a Senior AI & Python Developer to lead the design and development of AI-powered features across our platform. You will play a pivotal role in building scalable machine learning systems and integrating AI into our core product offerings. This is an exciting opportunity to work in a fast-paced, innovation-driven environment where your work directly impacts thousands of users. Key Responsibilities: - Design and implement scalable automation frameworks and tools to streamline business and engineering processes. - Lead the development and deployment of machine learning models and AI services tailored for our SaaS platform. - Work closely with cross-functional teams to identify opportunities for automation and streamline workflows to improve process efficiency. - Architect, write, and maintain clean, efficient Python code for AI pipelines and microservices. - Work with large datasets: data preprocessing, model training, evaluation, and optimization. - Drive the implementation of AI/ML features such as predictive analytics, intelligent recommendations, and automated decision-making. - Ensure robust monitoring, testing, and CI/CD practices for AI models in production. - Guide and mentor junior team members on AI best practices and coding standards. - Stay current with the latest AI research and industry trends and evaluate their relevance for product innovation. - Continuously evaluate and optimize existing processes to improve performance, reduce costs, and enhance scalability. Requirements: - Bachelors or masters degree in computer science, Data Science, Artificial Intelligence, or a related field. - 5+ years of professional experience in Python development. - 3+ years of hands-on experience in machine learning, deep learning, or applied AI. - Preferred experience supporting in the real estate and property management industry. - Proven track record of deploying ML models in production environments, preferably for SaaS applications. - Familiarity with ML Ops, model lifecycle management, and data versioning tools (e.g., MLflow, DVC). - Excellent problem-solving skills and the ability to work independently in a dynamic team environment. - Experience with generative AI (e.g., GPT, LLM fine-tuning or prompt engineering). - Background in NLP, computer vision, or recommender systems. - Experience working in Agile environments with tools like Jira, Confluence, or Notion.,

You should have at least 3+ years of relevant experience with the following skills: - Proficiency in Python, machine learning, deep learning, and NLP processing. - Experience in developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs. - Proficiency in Langchain, LLM. - Ability to prompt and optimize few-shot techniques to enhance LLM's performance on specific tasks. - Evaluate LLM's zero-shot and few-shot capabilities, fine-tuning hyperparameters, ensuring task generalization, and exploring model interpretability for robust web app integration. - Collaborate with ML and Integration engineers to leverage LLM's pre-trained potential, delivering contextually appropriate responses in a user-friendly web app. - Solid understanding of data structures, algorithms, and principles of software engineering. - Experience with vector databases RDBMS, MongoDB, and NoSQL databases. - Proficiency in working with embeddings. - Strong distributed systems skills and system architecture skills. - Experience in building and running a large platform at scale. - Hands-on experience with Python, Hugging Face, TensorFlow, Keras, PyTorch, Spark, or similar statistical tools. - Experience as a data modeling ML/NLP scientist, including performance tuning, fine-tuning, RLHF, and performance optimization. - Proficient with the integration of data from multiple sources and API design. - Good knowledge of Kubernetes and RESTful design. - Prior experience in developing public cloud services or open-source ML software is an advantage. You should also have a validated background with ML toolkits such as PyTorch, TensorFlow, Keras, Langchain, Llamadindex, SparkML, or Databricks. Your experience and strong knowledge of using AI/ML and particularly LLMs will be beneficial in this role.,

You will be a key member of our team as a Software Engineer specializing in AI. Your role will involve working at the cutting-edge intersection of advanced AI technologies and robust backend systems. We are seeking an individual with a strong background in Python development and a keen interest in creating scalable GenAI applications. Your primary responsibilities will revolve around designing, developing, and deploying backend services that support AI-driven systems and user experiences with a focus on LLM-based technologies. Your main tasks will include designing and implementing GenAI pipelines such as LLM orchestration, RAG, and multi-agent workflows using frameworks like LangChain, Agno, LlamaIndex, ReAct, AutoGen, or CrewAI. You will also be responsible for building and maintaining Python backend services utilizing FastAPI or Flask, creating APIs and microservices to expose LLM capabilities, integrating external data sources into AI workflows, and managing model selection, fine-tuning, and optimization for production use. Additionally, you will collaborate closely with product and design teams to translate user requirements into backend AI features. It would be advantageous if you have experience or interest in frontend technologies like React, Next.js, or Vue, as well as deploying applications in cloud environments using tools such as Docker, Kubernetes, and CI/CD pipelines. Familiarity with authentication systems, API gateways, and basic DevOps workflows is also a plus. Exposure to Python libraries for ML/AI such as Transformers, scikit-learn, PyTorch, and TensorFlow would be beneficial. To excel in this role, you should possess at least 4 years of professional experience in Python backend development and machine learning. Experience in building and deploying GenAI applications using LLMs and related orchestration frameworks is essential. A strong understanding of RESTful API design, backend architecture, vector databases, and FastAPI or Flask for production-grade services is required. Additionally, you should have a solid grasp of software engineering principles, testing methodologies, version control practices, and deployment procedures. A proactive mindset and the ability to thrive in dynamic environments are highly valued traits. We value individuals who exhibit ownership, pragmatism, curiosity, and collaboration. Ownership entails taking full responsibility for your work and outcomes, while pragmatism involves balancing innovation with reliability and scalability. Curiosity drives continuous learning and experimentation with new AI tools and trends, while collaboration fosters effective cross-disciplinary teamwork and clear communication. This position is offered as Contract-to-Hire, with the potential for full-time conversion based on your performance and fit within the team.,

As a part of this role, you will be responsible for setting up a Center of Excellence (CoE) and business practice for Enterprise AI solutions. You will be tasked with establishing Data Science & Analytics as a Service (DaaS) and building a practice with capabilities to create solution blueprints and roadmaps, orchestrate data acquisition, management, and engineering, as well as develop AI/ML models to solve analytical problems. It will be essential to stay updated with industry trends and developments to ensure the practice remains cutting-edge. In addition, you will promote collaboration and engagement within the team and with stakeholders. Your responsibilities will include creating technical Proof of Concepts (POCs) and solution demos, driving discussions to evaluate and design AI/ML solutions for various engagements, and implementing a framework across the solutions development lifecycle phases. You will also be required to develop a value tracking mechanism to monitor the Return on Investment (ROI) for AI/ML projects. Furthermore, a key aspect of this role will involve hiring, training, and mentoring a team of AI/ML experts to deliver technical solutions based on AI/ML products and platforms. It will be crucial to possess technical skills such as expertise in AI/ML, statistical modeling, ML techniques, and concepts, as well as experience with agile software development methodology and big-data projects. You should also have a fair understanding of verticals like Insurance, Manufacturing, and Education. Moreover, familiarity with tools and techniques related to data preparation, movement, analysis, visualization, machine learning, and Natural Language Processing (NLP) is essential. Experience in AI/ML enabled solution development leveraging high volume and high-velocity data across disparate systems and supporting large-scale Enterprise analytical solutions will be advantageous. Additionally, having a vision and the ability to set up solution practice groups will be beneficial. In terms of technical skills, it is required to have experience with Spark/Spark MLlib, visualization tools like Tableau/Power BI/Qlik View, cloud platforms such as Azure ML/AWS SageMaker/Snowflake, ML Ops, Automated ML, NLP, and Image/Video Analytics. Non-technical skills like possessing a master's degree in relevant fields, excellent interpersonal and people skills, analytical mindset, good debugging skills, and strong verbal and written English communication skills are also mandatory. Overall, this role offers a challenging opportunity to lead and drive AI/ML initiatives within the organization, requiring a combination of technical expertise, leadership skills, and a passion for innovation in the field of data science and analytics.,

You will be heading the Data Analytics and AI team within the Enterprise Technology Group with a primary purpose of leading and developing a robust team focused on driving the company towards a data-first and data-driven organization. Your role will involve delivering and maintaining smart data-driven solutions essential for growth and operational efficiency. Accelerating the adoption and implementation of AI solutions to enhance innovation and competitive advantage will be a key aspect. Managing all aspects of new data analytics and AI projects from inception to delivery, including day-to-day operations, will be crucial, with a strong emphasis on assessing business value, ROI, and cost reduction. The ideal candidate should hold a Bachelor's or Master's degree in Computer Science, Math, Quantitative Methods, or Information Systems, with over 10 years of overall technology experience, including substantial experience in data analytics and AI. Proficiency in programming languages such as Python, R, or similar, as well as a deep understanding of algorithms like linear regression, logistic regression, decision trees, random forest, boosting algorithms (e.g., XGBoost), k-means, hierarchical clustering, and principal component analysis is preferred. Familiarity with data science concepts, statistical and mathematical methods, and various Data & AI technologies/tools is essential. Located in Mumbai, this is a full-time office-based position within the Enterprise Technology Group, reporting to the Head of the same group. The key responsibilities will include leading and developing a strong data analytics and AI team, establishing best practices for data analytics and responsible AI initiatives, managing all stages of AI and LLM projects, collaborating with stakeholders to gather requirements, and implementing advanced models and algorithms to solve complex business problems. Staying updated with the latest advancements in AI and LLM technologies will also be a critical aspect of the role. Key behavioral strengths required for this position include excellent analytical, problem-solving, and decision-making skills, proven leadership abilities, effective communication and collaboration skills, and the capacity to work with diverse stakeholders. Joining CulverMax Entertainment Pvt Ltd will offer you the opportunity to work with some of India's leading entertainment channels and OTT platforms, alongside a progressive and inclusive work culture that celebrates diversity and innovation. As a part of the team, you will contribute to creating exceptional content and experiences while being recognized as an Employer of Choice in various prestigious awards and accolades.,

As an individual contributor at Adobe, you will play a pivotal role in driving innovation and shaping the future of digital experiences. Adobe is dedicated to fostering a work environment where every employee is valued, respected, and provided with equal opportunities. Your insights and ideas are highly valued as we strive to build exceptional products and services that cater to a global audience. The opportunity at hand involves working on a cutting-edge Component Content Management System that powers structured content for large enterprises. In this role, you will collaborate with cross-functional teams to identify key project interfaces and implement complex Machine Learning (ML) solutions using technologies such as Natural Language Processing (NLP), Generative AI, and Transformer architectures. Your responsibilities will include developing, evaluating, and deploying scalable ML models, monitoring their performance, and continuously enhancing Adobe's products and services. To excel in this role, you should possess a master's degree or equivalent experience in Machine Learning, with a minimum of 10 years of combined industry experience in ML, software engineering, and data engineering. Proficiency in Python, ML frameworks like PyTorch and TensorFlow, as well as strong programming skills in languages such as Python and Java, are essential. Additionally, you should have a solid understanding of ML Ops, data analysis, and mining using frameworks like Hadoop and Spark. Your ability to drive innovation, collaborate effectively, and adapt to an ever-evolving technological landscape will be crucial in this role. Strong problem-solving skills, excellent communication abilities, and a passion for staying abreast of the latest technological advancements are highly valued. In this dynamic and fast-paced environment, you will have the opportunity to contribute to the growth and success of Adobe while working alongside a diverse and inclusive team. If you are seeking a challenging yet rewarding opportunity to make a significant impact, Adobe is the place for you. Join us in creating exceptional digital experiences and pushing the boundaries of innovation. Explore the possibilities of a career at Adobe by updating your profile and applying for roles that align with your expertise and aspirations. Your journey towards professional growth and accomplishment starts here.,

As the AI Ops, ML Ops, and LLM Ops Manager, your primary responsibility is to oversee the efficient and scalable operations of AI and machine learning models. You will be in charge of managing the entire model lifecycle, covering development, deployment, monitoring, and maintenance. It is crucial to ensure strict adherence to predefined Service Level Agreements (SLAs) for AI and ML operations. To streamline the integration and deployment of models, you will be required to develop and maintain CI/CD Ops pipelines. Additionally, implementing and managing model registries for version control and governance is essential. You will establish coding checklists and best practices while also developing and automating testing frameworks to maintain model quality and reliability. Designing and managing inference pipelines for both real-time and batch predictions will be under your purview. Innovation plays a key role in this role, as you will be expected to adopt emerging technologies such as GenAI, AI, and NLP. Accelerating product/service development through rapid prototyping and iterative methods will be necessary to drive innovation effectively. Furthermore, aligning analytics innovation efforts with business strategy, IT strategy, and legal/regulatory requirements is imperative. You will also be tasked with identifying and developing advanced analytics capabilities and ecosystem partnerships in alignment with the DnA strategy. Key Responsibilities: - Lead AI Ops, ML Ops, and LLM Ops to ensure efficient and scalable operation of AI and machine learning models. - Develop and manage the model lifecycle, including development, deployment, monitoring, and maintenance. - Ensure adherence to predefined SLAs for AI and ML operations. - Create and manage analytics product/services roadmaps from concept to launch. - Develop and maintain CI/CD Ops pipelines for seamless integration and deployment of models. - Implement and manage model registries for version control and governance. - Establish and enforce coding checklists and best practices. - Develop and automate testing frameworks to ensure model quality and reliability. - Design and manage inference pipelines for real-time and batch predictions. - Incubate and adopt emerging technologies (GenAI, AI, NLP) to accelerate product/service development through rapid prototyping and iterative methods. - Align analytics innovation efforts with business strategy, IT strategy, and legal/regulatory requirements. - Establish and update strategies, implementation plans, and value cases for emerging technologies. - Drive innovation using appropriate people, processes, partners, and tools. - Identify and develop advanced analytics capabilities and ecosystem partnerships in alignment with DnA strategy. - Oversee end-to-end delivery of analytics services and products across cross-functional business areas. - Serve as the point of escalation, review, and approval for key issues and decisions. - Manage resource and capacity planning in line with business priorities and strategies. - Foster continuous improvement within the team. - Decide on program timelines, governance, and deployment strategies. Key Performance Indicators: - Achieved targets in Enterprise business case contribution, KPIs, customer satisfaction, and innovation measures. - Delivery on agreed KPIs including business impact - Launch of innovative technology solutions across Novartis at scale. - Business impact and value generated from DDIT solutions. - Adoption and development of Agile Productization and DevOps practices. - Operations stability and effective risk management. - Feedback on customer experience. - Applications adherence to ISC requirements and are audit ready. - Business capability, vision & strategy clearly defined, communicated, and executed, well aligned to business strategy and Enterprise IT strategy, providing a competitive advantage to Novartis. - Role model with the highest standards of professional conduct in leading the business capability area in line with the new IT operating model. - Deployment of digital platforms and services at scale to deliver the digital strategy. Skills And Experience: - Demonstrated experience in Budget Management, Business Acumen, Performance Management, Planning, Project Management, Risk Management, Service Delivery Management, and stakeholder management. - Strong understanding of AI Ops, ML Ops, and LLM Ops. - Experience in developing and managing the model lifecycle, including deployment and maintenance. - Proficiency in managing operations with predefined SLAs. - Expertise in CI/CD Ops pipelines development. - Experience with model registry and management. - Knowledge of coding checklists and best practices. - Proficiency in developing and automating testing frameworks. - Experience in designing and managing inference pipelines. - Production experience with commercial and open-source ML platforms. - Strong knowledge of AWS, Databricks, and Snowflake service offerings. - Ability to collaborate with business teams to gather requirements, groom product backlogs, and drive delivery. - Agile delivery experience managing multiple concurrent delivery cycles. - Solid foundation in CRISP analytical life cycle management. - Strong leadership skills with the ability to build high-performing teams. - Excellent vendor management and IT governance skills. - Innovative and analytical mindset with a focus on continuous improvement. - Emerging Technology Monitoring, Consulting, Influencing & persuading, Unbossed Leadership, IT governance, Building High Performing Teams, Vendor Management, Innovative & Analytical Technologies. - Strong understanding of descriptive vs. prescriptive Analytical frameworks. - Strong knowledge of visualization platforms and project life cycle management, including Power BI, Qlik, and MicroStrategy. - Significant production experience addressing visualization platform and data pipeline performance constraints. - Strong analytical and problem-solving skills, effective communication, and the ability to influence and collaborate with cross-functional teams.,

As a Manager, ML Ops Engineer at Genpact, you will be an integral part of the team responsible for building and maintaining the infrastructure and pipelines for cutting-edge Generative AI applications. Your role will involve collaborating closely with the Generative AI Full Stack Architect to ensure the efficiency, scalability, and reliability of Generative AI models in production. Your responsibilities will include designing, developing, and implementing ML/LLM pipelines for generative AI models, conducting research to explore new techniques, integrating GenAI APIs and microservices into existing systems, and automating ML tasks across the model lifecycle using tools like GitOps, CI/CD pipelines, and containerization technologies. Furthermore, you will be involved in MLOps support and maintenance on ML platforms Dataiku/Sagemaker, implementing version control, CI/CD pipelines, and containerization techniques, designing monitoring and alerting systems, and collaborating with infrastructure and DevOps teams for resource management. To qualify for this role, you should have a Bachelor's degree in computer science, Data Science, Engineering, or a related field, along with a deep understanding of generative AI concepts and experience in MLOps or related areas. Strong expertise in cloud platforms, CI/CD principles, containerization technologies, and monitoring tools is essential. Excellent communication, collaboration, and problem-solving skills are also required, along with a passion for Generative AI and its potential to transform industries. If you are looking to join a dynamic team at Genpact and contribute to the advancement of Generative AI technologies, we encourage you to apply for the Manager, ML Ops Engineer position in India-Bangalore. This is a full-time role with the opportunity to work on cutting-edge projects and make a significant impact in the field of AI. Join us on this exciting journey to shape the future with your expertise in ML Ops and Generative AI!,