360 Aws Sagemaker Jobs - Page 7

Hiring an ML Engineer immediate joiner for the Hyderabad/Chennai/Pune/Noida location(Hybrid) Role & responsibilities 8+ n Machine Learning Engineering Strong programming skills in Python with experience in libraries such as scikit-learn, torch, pandas, scipy, click, and flask and/or FastAPI. Experience with the AWS ecosystem ( AWS SageMaker ) Strong understanding of ML algorithms, techniques, and best practices. Strong programming skills in python and Data analytical expertise

Experience: 5+ years of experience in AWS cloud engineering or related roles. Proven experience managing AWS services, including Amazon Q, SageMaker, Bedrock, Lambda, S3, and RDS. Technical Skills: Strong expertise in AWS services and cloud architecture. Knowledge of containerization technologies (Docker, Kubernetes). Familiarity with CI/CD tools (AWS CodePipeline, Jenkins). Proficient in scripting languages (Python, Bash) for automation tasks. FinOps Skills: Experience with Cloud Financial Management (FinOps) principles and practices. Ability to analyze cloud spending and recommend cost-saving measures. Soft Skills: Excellent problem-solving skills and attention to detail. Strong communication and collaboration abilities. Ability to work in a fast-paced, agile environment. Preferred Qualifications AWS Certified Solutions Architect or DevOps Engineer. Experience with machine learning and data analytics platforms on AWS. Familiarity with risk management frameworks and compliance standards.

Qualifications Education: Bachelors degree in Computer Science, Information Technology, or a related field. Experience: 5+ years of experience in AWS cloud engineering or related roles. Proven experience managing AWS services, including Amazon Q, SageMaker, Bedrock, Lambda, S3, and RDS. Technical Skills: Strong expertise in AWS services and cloud architecture. Knowledge of containerization technologies (Docker, Kubernetes). Familiarity with CI/CD tools (AWS CodePipeline, Jenkins). Proficient in scripting languages (Python, Bash) for automation tasks. FinOps Skills: Experience with Cloud Financial Management (FinOps) principles and practices. Ability to analyze cloud spending and recommend cost-saving measures. Soft Skills: Excellent problem-solving skills and attention to detail. Strong communication and collaboration abilities. Ability to work in a fast-paced, agile environment. Preferred Qualifications AWS Certified Solutions Architect or DevOps Engineer. Experience with machine learning and data analytics platforms on AWS. Familiarity with risk management frameworks and compliance standards.

Role & responsibilities 5+ in Machine Learning Engineering Strong programming skills in Python with experience in libraries such as scikit-learn, torch, pandas, scipy, click, and flask and/or FastAPI. Experience with the AWS ecosystem ( AWS SageMaker ) Strong understanding of ML algorithms, techniques, and best practices. Strong programming skills in python and Data analytical expertise

As an Associate Project Manager specializing in AI/ML, you will leverage your 8+ years of experience, including 3+ years in project management, to lead and oversee the successful delivery of AI/ML projects. You will play a pivotal role in managing cross-functional teams, steering complex software projects, and spearheading AI/ML initiatives from inception to deployment. Your expertise will encompass a blend of project management proficiency and technical knowledge in machine learning systems, data pipelines, and model lifecycle management. Your responsibilities will include project planning, tracking, and execution, utilizing methodologies such as Agile, Scrum, and SDLC/Waterfall. You will demonstrate your ability to juggle multiple projects and stakeholders across both business and technical domains, while also showcasing your skills in budgeting, vendor negotiation, and resource planning. Proficiency in tools like MS Project, Excel, PowerPoint, ServiceNow, SmartSheet, and Lucidchart will be essential for effective project management. Technical exposure in AI/ML is a must-have for this role, encompassing familiarity with the AI/ML project lifecycle, ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn), and data platforms (e.g., Azure ML, AWS SageMaker, Databricks). You will be well-versed in MLOps practices, model versioning, and CI/CD pipelines for ML, collaborating closely with data scientists, ML engineers, and DevOps teams to deliver innovative AI/ML solutions. Your ability to translate business challenges into AI/ML use cases and efficiently manage delivery timelines will be paramount. In addition to your technical acumen, you will exhibit strong leadership qualities, effective decision-making skills, and impeccable organizational abilities. Your excellent communication and stakeholder management aptitudes will enable you to influence and secure buy-in from executive sponsors and cross-functional teams. Building and nurturing relationships with business leaders and technical stakeholders will be crucial for the success of AI/ML projects under your purview. Your roles and responsibilities will include leading AI/ML and software development projects end-to-end, collaborating with data science and engineering teams to define project scope and deliverables, and maintaining detailed project plans aligned with business objectives. You will monitor progress, mitigate risks, ensure timely delivery of AI/ML models and software components, and facilitate alignment between business, data, and engineering stakeholders. Tracking project metrics, ROI, and model performance post-deployment, while ensuring compliance with data governance, security, and ethical AI standards, will be integral to your responsibilities. Continuous improvement in project execution and delivery frameworks, staying abreast of AI/ML trends, and contributing to strategic planning for future initiatives will be key aspects of your role as an Associate Project Manager in AI/ML.,

Are you seeking an exciting opportunity to join a dynamic and growing team in a fast-paced and challenging environment This unique role offers you the chance to collaborate with the Business team and provide a comprehensive view. As a Data Scientist Analyst in Asset and Wealth Management Risk within our AWM Risk team, you will play a senior role in our journey of innovation. Your primary focus will be on introducing and scaling up data-driven risk analytics solutions through the application of data science and machine learning techniques. Your contributions will transform our operations and business processes, enhancing the core value proposition of our system and expanding flexible analytical capabilities for the growth of Newton's platform. JPMorgan Asset & Wealth Management Risk (AWM) is actively seeking a dynamic Risk professional with strong quantitative analysis skills to join our AWM Risk Analytics team. This team, a pivotal part of AWM Risk Management, comprises a diverse group of innovative quantitative and market risk-oriented professionals. Our key responsibilities include developing and maintaining risk measurement methodologies, conducting analytics calculations, and overseeing the AWM Risk System (Newton) used by AWM Risk Management and Front Office stakeholders. Your responsibilities in this role will include: - Collaborating with peers and stakeholders to identify use cases for Data Science that create value, utilizing your expertise in Computer Science, Statistics, Mathematics, and Data Science techniques for security and portfolio risk analytics. - Leading continuous improvements in AI/ML and statistical techniques used in data and analytics validation processes. - Designing and delivering scalable solutions using approved new technologies and tools, such as AI and LLMs, leveraging the citizen developer journey platform to enhance process efficiencies. - Contributing to the analysis of new and large data sets, adhering to best practice data modeling and architecture using big data platforms. - Contributing to the research and enhancement of the risk methodology for AWM Risk Analytics, covering sensitivity, stress, VaR, factor modeling, and Lending Value pricing for investment, counterparty, and liquidity risk. Required qualifications, capabilities, and skills: - Minimum 6 months of experience as a Data Scientist or in a related quantitative role. - Detail-oriented, technically proficient individual with the ability to multitask and work independently. - Excellent communication skills. - Strong understanding of statistics, applied AI/ML techniques, and a practical problem-solving mindset. - Knowledge in modular programming in SQL, Python, ML, AWS Sagemaker, TensorFlow, or similar tools. Preferred qualifications, capabilities, and skills include: - Practical experience in financial markets within Risk Management or a Front Office role. - Knowledge of asset pricing, VaR backtesting techniques, and model performance testing. Join us in this exciting opportunity to contribute to cutting-edge data-driven risk analytics solutions within the Asset and Wealth Management Risk sector.,

Summary: We are seeking an experienced AI Engineer with 4 to 5 years of experience to join our team. The ideal candidate will have a strong background in artificial intelligence and machine learning technologies, as well as a proven track record of developing innovative solutions. Roles and Responsibilities: - Design and develop AI algorithms and models to solve complex business problems - Implement and optimize machine learning algorithms for real-time applications - Collaborate with cross-functional teams to integrate AI solutions into existing systems - Conduct research and stay up-to-date on the latest advancements in AI technology - Provide technical guidance and mentorship to junior team members - Participate in code reviews and contribute to the overall software development process Qualifications: - Bachelor's degree in Computer Science, Engineering, or related field - 4 to 5 years of experience in AI development - Strong programming skills in languages such as Python, Java, or C++ - Experience working with Langchain, LangGraph, and vector databases (e.g., Pinecone, ChromaDB, FAISS). - Hands-on experience with Hugging Face ecosystem including transformers etc. - Proficiency in model serving and deployment, using tools like FastAPI, Hugging Face Inference Endpoints, or AWS SageMaker for scalable and production-grade AI applications. - Strong understanding of prompt engineering, retrieval-augmented generation (RAG), and tokenization/token-level optimization. - Proven experience with fine-tuning and deploying LLMs (e.g., LLaMA, Mistral, Falcon, OpenAI, or Hugging Face Transformers). -Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn - Knowledge of cloud computing platforms such as AWS or Azure - Excellent problem-solving and analytical skills - Strong communication and teamwork abilities

As an AI/ML Manager at our Pune location, you will be responsible for leading the development of machine learning proof of concepts (PoCs) and demos using structured/tabular data for various use cases like forecasting, risk scoring, churn prediction, and optimization. Your role will involve collaborating with sales engineering teams to understand client requirements and presenting ML solutions during pre-sales calls and technical workshops. You will be expected to build ML workflows using tools such as SageMaker, Azure ML, or Databricks ML, managing training, tuning, evaluation, and model packaging. Applying supervised, unsupervised, and semi-supervised techniques like XGBoost, CatBoost, k-Means, PCA, and time-series models will be a key part of your responsibilities. Working closely with data engineering teams, you will define data ingestion, preprocessing, and feature engineering pipelines using Python, Spark, and cloud-native tools. Packaging and documenting ML assets for scalability and transition into delivery teams post-demo will be essential. Staying updated with the latest best practices in ML explainability, model performance monitoring, and MLOps practices is also expected. Participation in internal knowledge sharing, tooling evaluation, and continuous improvement of lab processes are additional aspects of this role. To qualify for this position, you should have at least 8+ years of experience in developing and deploying classical machine learning models in production or PoC environments. Strong hands-on experience with Python, pandas, scikit-learn, and ML libraries like XGBoost, CatBoost, LightGBM is required. Familiarity with cloud-based ML environments such as AWS SageMaker, Azure ML, or Databricks is preferred. A solid understanding of feature engineering, model tuning, cross-validation, and error analysis is necessary. Experience with unsupervised learning, clustering, anomaly detection, and dimensionality reduction techniques will be beneficial. You should be comfortable presenting models and insights to both technical and non-technical stakeholders during pre-sales engagements. Working knowledge of MLOps concepts, including model versioning, deployment automation, and drift detection, will be an advantage. If you are interested in this opportunity, please apply or share your resume at kanika.garg@austere.co.in.,

HCLTech is seeking a Data and AI Principal / Senior Manager (Generative AI) for their Noida location. As a global technology company with a workforce of over 218,000 employees in 59 countries, HCLTech specializes in digital, engineering, cloud, and AI solutions. The company collaborates with clients across various industries such as Financial Services, Manufacturing, Life Sciences, Healthcare, Technology, Telecom, Retail, and Public Services, offering innovative technology services and products. With consolidated revenues of $13.7 billion as of the 12 months ending September 2024, HCLTech aims to drive progress and transformation for its clients globally. Key Responsibilities: In this role, you will be responsible for providing hands-on technical leadership and oversight, including leading the design of AI and GenAI solutions, machine learning pipelines, and data architectures. You will actively contribute to coding, solution design, and troubleshooting critical components, collaborating with Account Teams, Client Partners, and Domain SMEs to ensure technical solutions align with business needs. Additionally, you will mentor and guide engineers across various functions to foster a collaborative and high-performance team environment. As part of the role, you will design and implement system and API architectures, integrating microservices, RESTful APIs, cloud-based services, and machine learning models seamlessly into GenAI and data platforms. You will lead the integration of AI, GenAI, and Agentic applications, NLP models, and large language models into scalable production systems. You will also architect ETL pipelines, data lakes, and data warehouses using tools like Apache Spark, Airflow, and Google BigQuery, and drive deployment using cloud platforms such as AWS, Azure, and GCP. Furthermore, you will lead the design and deployment of machine learning models using frameworks like PyTorch, TensorFlow, and scikit-learn, ensuring accurate and reliable outputs. You will develop prompt engineering techniques for GenAI models and implement best practices for ML model performance monitoring and continuous training. The role also involves expertise in CI/CD pipelines, Infrastructure-as-Code, cloud management, stakeholder communication, agile development, performance optimization, and scalability strategies. Required Qualifications: - 15+ years of hands-on technical experience in software engineering, with at least 5+ years in a leadership role managing cross-functional teams in AI, GenAI, machine learning, data engineering, and cloud infrastructure. - Proficiency in Python and experience with Flask, Django, or FastAPI for API development. - Extensive experience in building and deploying ML models using TensorFlow, PyTorch, scikit-learn, and spaCy, and integrating them into AI frameworks. - Familiarity with ETL pipelines, data lakes, data warehouses, and data processing tools like Apache Spark, Airflow, and Kafka. - Strong expertise in CI/CD pipelines, containerization, Infrastructure-as-Code, and API security for high-traffic systems. If you are interested in this position, please share your profile with the required details including Overall Experience, Skills, Current and Preferred Location, Current and Expected CTC, and Notice Period to paridhnya_dhawankar@hcltech.com.,

The ideal candidate for this position in Ahmedabad should be a graduate with at least 3 years of experience. At Bytes Technolab, we strive to create a cutting-edge workplace infrastructure that empowers our employees and clients. Our focus on utilizing the latest technologies enables our development team to deliver high-quality software solutions for a variety of businesses. You will be responsible for leveraging your 3+ years of experience in Machine Learning and Artificial Intelligence to contribute to our projects. Proficiency in Python programming and relevant libraries such as NumPy, Pandas, and scikit-learn is essential. Hands-on experience with frameworks like PyTorch, TensorFlow, Keras, Facenet, and OpenCV will be key in your role. Your role will involve working with GPU acceleration for deep learning model development using CUDA, cuDNN. A strong understanding of neural networks, computer vision, and other AI technologies will be crucial. Experience with Large Language Models (LLMs) like GPT, BERT, LLaMA, and familiarity with frameworks such as LangChain, AutoGPT, and BabyAGI are preferred. You should be able to translate business requirements into ML/AI solutions and deploy models on cloud platforms like AWS SageMaker, Azure ML, and Google AI Platform. Proficiency in ETL pipelines, data preprocessing, and feature engineering is required, along with experience in MLOps tools like MLflow, Kubeflow, or TensorFlow Extended (TFX). Expertise in optimizing ML/AI models for performance and scalability across different hardware architectures is necessary. Knowledge of Natural Language Processing (NLP), Reinforcement Learning, and data versioning tools like DVC or Delta Lake is a plus. Skills in containerization tools like Docker and orchestration tools like Kubernetes will be beneficial for scalable deployments. You should have experience in model evaluation, A/B testing, and establishing continuous training pipelines. Working in Agile/Scrum environments with cross-functional teams, understanding ethical AI principles, model fairness, and bias mitigation techniques are important. Familiarity with CI/CD pipelines for machine learning workflows and the ability to communicate complex concepts to technical and non-technical stakeholders will be valuable.,

At PwC, our data and analytics team focuses on utilizing data to drive insights and support informed business decisions. We leverage advanced analytics techniques to assist clients in optimizing their operations and achieving strategic goals. As a data analysis professional at PwC, your role will involve utilizing advanced analytical methods to extract insights from large datasets, enabling data-driven decision-making. Your expertise in data manipulation, visualization, and statistical modeling will be pivotal in helping clients solve complex business challenges. PwC US - Acceleration Center is currently seeking a highly skilled MLOps/LLMOps Engineer to play a critical role in deploying, scaling, and maintaining Generative AI models. This position requires close collaboration with data scientists, ML/GenAI engineers, and DevOps teams to ensure the seamless integration and operation of GenAI models within production environments at PwC and for our clients. The ideal candidate will possess a strong background in MLOps practices and a keen interest in Generative AI technologies. With a preference for candidates with 4+ years of hands-on experience, core qualifications for this role include: - 3+ years of experience developing and deploying AI models in production environments, alongside 1 year of working on proofs of concept and prototypes. - Proficiency in software development, including building and maintaining scalable, distributed systems. - Strong programming skills in languages such as Python and familiarity with ML frameworks like TensorFlow and PyTorch. - Knowledge of containerization and orchestration tools like Docker and Kubernetes. - Understanding of cloud platforms such as AWS, GCP, and Azure, including their ML/AI service offerings. - Experience with continuous integration and delivery tools like Jenkins, GitLab CI/CD, or CircleCI. - Familiarity with infrastructure as code tools like Terraform or CloudFormation. Key Responsibilities: - Develop and implement MLOps strategies tailored for Generative AI models to ensure robustness, scalability, and reliability. - Design and manage CI/CD pipelines specialized for ML workflows, including deploying generative models like GANs, VAEs, and Transformers. - Monitor and optimize AI model performance in production, utilizing tools for continuous validation, retraining, and A/B testing. - Collaborate with data scientists and ML researchers to translate model requirements into scalable operational frameworks. - Implement best practices for version control, containerization, and orchestration using industry-standard tools. - Ensure compliance with data privacy regulations and company policies during model deployment. - Troubleshoot and resolve issues related to ML model serving, data anomalies, and infrastructure performance. - Stay updated with the latest MLOps and Generative AI developments to enhance AI capabilities. Project Delivery: - Design and implement scalable deployment pipelines for ML/GenAI models to transition them from development to production environments. - Oversee the setup of cloud infrastructure and automated data ingestion pipelines to meet GenAI workload requirements. - Create detailed documentation for deployment pipelines, monitoring setups, and operational procedures. Client Engagement: - Collaborate with clients to understand their business needs and design ML/LLMOps solutions. - Present technical approaches and results to technical and non-technical stakeholders. - Conduct training sessions and workshops for client teams. - Create comprehensive documentation and user guides for clients. Innovation And Knowledge Sharing: - Stay updated with the latest trends in MLOps/LLMOps and Generative AI. - Develop internal tools and frameworks to accelerate model development and deployment. - Mentor junior team members and contribute to technical publications. Professional And Educational Background: - Any graduate / BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Masters Degree / MBA,

As a Python Engineer with 2-4 years of experience, you will be responsible for building, deploying, and scaling Python applications along with AI/ML solutions. Your strong programming skills will be put to use in developing intelligent solutions and collaborating closely with clients and software engineers to implement machine learning models. You should be an expert in Python, with advanced knowledge of Flask/FastAPI and server programming to implement complex business logic. Understanding fundamental design principles behind scalable applications is crucial. Independently designing, developing, and deploying machine learning models and AI algorithms tailored to business requirements will be a key aspect of your role. Your responsibilities will include solving complex technical challenges through innovative AI/ML solutions, building and maintaining integrations (e.g., APIs) for machine learning models, conducting data preprocessing and feature engineering, and optimizing datasets for model training and inference. Monitoring and continuously improving model performance in production environments, focusing on scalability and efficiency, will also be part of your tasks. Managing model deployment, monitoring, and scaling using tools like Docker, Kubernetes, and cloud services will be essential. You will need to develop integration strategies for smooth communication between APIs and troubleshoot integration issues. Creating and maintaining comprehensive documentation for AI/ML projects will be necessary, along with staying updated on emerging trends and technologies in AI/ML. Key Skills Required: - Proficiency in Python, R, or similar languages commonly used in ML/AI development - Hands-on experience with TensorFlow, PyTorch, scikit-learn, or similar ML libraries - Strong knowledge of data preprocessing, data cleaning, and feature engineering - Familiarity with model deployment using Docker, Kubernetes, or cloud platforms - Understanding of statistical methods, probability, and data-driven decision-making processes - Proficient in querying databases for ML projects - Experience with ML lifecycle management tools like MLflow, Kubeflow - Familiarity with NLP frameworks for language-based AI solutions - Exposure to computer vision techniques - Experience with managed ML services like AWS SageMaker, Azure Machine Learning, or Google Cloud AI Platform - Familiarity with agile workflows and DevOps or CI/CD pipelines Good to Have Skills: - Exposure to big data processing tools like Spark, Hadoop - Experience with agile development methodologies The job location for this role is in Ahmedabad/Pune, and the required educational qualifications include a UG degree in BE/BTech or PG degree in ME/M-Tech/MCA/MSC-IT/Data Science, AI, Machine Learning, or a related field.,

You will be joining our innovative EdTech team as an experienced AI/ML Content Developer. Your primary responsibility will be to create cutting-edge educational content in the field of artificial intelligence and machine learning. You will play a key role in developing comprehensive courses that cover a wide range of AI/ML domains, starting from foundational machine learning concepts to advanced generative AI and agentic AI systems. This position presents an exciting opportunity for you to influence how the next generation of AI practitioners learn and apply these transformative technologies. In this role, your tasks will include designing and developing comprehensive courses across AI/ML domains such as machine learning, natural language processing, computer vision, generative AI, and agentic AI systems. You will create diverse content formats, including hands-on labs, interactive exercises, assessments, and project-based learning modules. Additionally, you will structure learning paths that logically progress from foundational concepts to advanced AI applications. You will also develop practical coding exercises and real-world implementation scenarios using industry-standard tools and frameworks. Ensuring the quality and industry relevance of the content will be a crucial aspect of your role. You will need to ensure that all content reflects current AI/ML best practices and stays aligned with rapidly evolving industry trends. Creating practical, real-world scenarios that simulate actual AI development workflows and challenges will be part of your responsibilities. You will also collaborate with our instructional design team to optimize learning outcomes for complex technical concepts. Furthermore, you will work closely with our platform team to ensure the seamless delivery of AI/ML content and interactive experiences. Continuous iteration and improvement of existing content based on learner feedback and performance metrics will be essential. Staying updated with the latest AI research, tools, and educational methodologies, as well as integrating emerging AI technologies and frameworks into the curriculum as they become industry-relevant, will also be part of your role. For this position, we are looking for candidates with 3+ years of hands-on industry experience in machine learning, AI development, or related technical roles. Essential qualifications include domain expertise in machine learning algorithms, deep learning architectures, and AI system design. Proficiency in Python and core data science libraries, experience with machine learning frameworks like PyTorch and TensorFlow, and expertise in natural language processing techniques are also required. Additionally, strong communication skills, the ability to explain complex AI concepts clearly, and experience in creating technical AI/ML content are essential for this role. Preferred qualifications include an advanced degree (Master's/PhD) in Computer Science, Machine Learning, Data Science, or a related field, published research in AI/ML conferences or journals, experience with reinforcement learning and multi-agent systems, familiarity with AI safety, ethics, and responsible AI development practices, and knowledge of emerging AI architectures and research trends. Background in technical training, workshops, or mentoring in AI/ML domains and an understanding of accessibility standards in educational content are also desirable.,

We Are Hiring MLOps Engineer Location: Hyderabad / Trivandrum / Kochi Skills: MLOps, Python, AWS, SageMaker, CI/CD Pipeline Experience: 4+ Years Notice Period: 015 Days Only Note: All the above skills must be clearly mentioned in your CV – mandatory requirement. Share your CV: shivani.awadhiya@alikethoughts.com ***Immediate Joinner Only send CV in MAil or apply here*** Relocation Also apply here

HCLTech is looking for a Data and AI Principal / Senior Manager (Generative AI) to join their team in Noida. As a global technology company with a strong presence in 59 countries and over 218,000 employees, HCLTech is a leader in digital, engineering, cloud, and AI services. They collaborate with clients in various industries such as Financial Services, Manufacturing, Life Sciences, Healthcare, Technology, Telecom, Media, Retail, and Public Services. With consolidated revenues of $13.7 billion, HCLTech aims to provide industry-leading capabilities to drive progress for their clients. In this role, you will be responsible for providing hands-on technical leadership and oversight. This includes leading the design of AI, GenAI solutions, machine learning pipelines, and data architectures to ensure performance, scalability, and resilience. You will actively contribute to coding, code reviews, and solution design, while working closely with Account Teams, Client Partners, and Domain SMEs to align technical solutions with business needs. Mentoring and guiding engineers across various functions will be an essential aspect of this role, fostering a collaborative and high-performance team environment. Your role will also involve designing and implementing system and API architectures, integrating AI, GenAI, and Agentic applications into production systems, and architecting ETL pipelines, data lakes, and data warehouses using industry-leading tools. You will drive the deployment and scaling of solutions using cloud platforms like AWS, Azure, and GCP, while leading the integration of machine learning models into end-to-end production workflows. Additionally, you will be responsible for leading CI/CD pipeline efforts, infrastructure automation, and ensuring robust integration with cloud platforms. Stakeholder communication, promoting Agile methodologies, and optimizing performance and scalability of applications will be key responsibilities. The ideal candidate will have at least 15 years of hands-on technical experience in software engineering, with a focus on AI, GenAI, machine learning, data engineering, and cloud infrastructure. If you meet the qualifications and are passionate about driving innovation in AI and data technologies, we invite you to share your profile with us. Kindly email your details to paridhnya_dhawankar@hcltech.com including your overall experience, skills, current and preferred location, current and expected CTC, and notice period. We look forward to hearing from you and exploring the opportunity to work together at HCLTech.,

You are an experienced AI/ML Content Developer who will be joining an innovative EdTech team. Your primary responsibility will involve creating cutting-edge educational content in artificial intelligence and machine learning. This includes developing comprehensive courses covering various AI/ML domains such as machine learning, natural language processing, computer vision, generative AI, and agentic AI systems. Your role will be pivotal in shaping how the next generation of AI practitioners learn and apply these transformative technologies. Your key responsibilities will include designing and developing comprehensive courses, content creation in various formats like hands-on labs, interactive exercises, assessments, and project-based learning modules. You will also be structuring learning paths logically from foundational concepts to advanced AI applications. Practical coding exercises and real-world implementation scenarios using industry-standard tools and frameworks will be a significant part of your role. Ensuring that all content reflects current AI/ML best practices and industry trends will be crucial. You will be creating practical, real-world scenarios that replicate AI development workflows and challenges. Moreover, developing hands-on projects involving model training, fine-tuning, and deployment to provide learners with portfolio-worthy experience will be essential. Collaboration with the instructional design team to optimize learning outcomes for complex technical concepts is also expected. You will work closely with the platform team to ensure the seamless delivery of AI/ML content and interactive experiences. Continuous iteration and improvement of existing content based on learner feedback and performance metrics will be part of your responsibilities. Staying current with the latest AI research, tools, and educational methodologies is necessary. Additionally, integrating emerging AI technologies and frameworks into the curriculum as they become industry-relevant is also expected. To qualify for this role, you should have at least 3+ years of hands-on industry experience in machine learning, AI development, or related technical roles. Domain expertise in machine learning algorithms, deep learning architectures, and AI system design is required. Proficiency in Python and core data science libraries, experience with machine learning frameworks like PyTorch and/or TensorFlow, and expertise in natural language processing techniques are necessary technical skills. Strong communication skills, the ability to explain complex AI concepts clearly, and experience in creating compelling narratives around AI applications and use cases are also essential. Preferred qualifications include an advanced degree (Master's/PhD) in Computer Science, Machine Learning, Data Science, or related fields, published research in AI/ML conferences or journals, experience with reinforcement learning and multi-agent systems, familiarity with AI safety, ethics, and responsible AI development practices, and knowledge of emerging AI architectures and research trends. Background in technical training, workshops, or mentoring in AI/ML domains and understanding of accessibility standards in educational content are also desirable.,

At PwC, we focus on leveraging data to drive insights and make informed business decisions in the field of data and analytics. Our team utilises advanced analytics techniques to help clients optimize their operations and achieve their strategic goals. As a Data Analyst at PwC, you will play a crucial role in utilizing advanced analytical techniques to extract insights from large datasets and facilitate data-driven decision-making. Your responsibilities will include leveraging skills in data manipulation, visualization, and statistical modeling to assist clients in solving complex business problems. We are currently seeking a highly skilled MLOps/LLMOps Engineer to join PwC US - Acceleration Center. In this role, you will be responsible for the deployment, scaling, and maintenance of Generative AI models. Working closely with data scientists, ML/GenAI engineers, and DevOps teams, you will ensure seamless integration and operation of GenAI models within production environments at PwC and our clients. The ideal candidate will have a strong background in MLOps practices, coupled with experience and interest in Generative AI technologies. As a candidate, you should have a minimum of 4+ years of hands-on experience. Core qualifications for this role include 3+ years of experience developing and deploying AI models in production environments, with a year of experience in developing proofs of concept and prototypes. Additionally, a strong background in software development, proficiency in programming languages like Python, knowledge of ML frameworks and libraries, familiarity with containerization and orchestration tools, and experience with cloud platforms and CI/CD tools are essential. Key responsibilities of the role involve developing and implementing MLOps strategies tailored for Generative AI models, designing and managing CI/CD pipelines specialized for ML workflows, monitoring and optimizing the performance of AI models in production, collaborating with data scientists and ML researchers, and ensuring compliance with data privacy regulations. You will also be responsible for troubleshooting and resolving issues related to ML model serving, data anomalies, and infrastructure performance. The successful candidate will be proficient in MLOps tools such as MLflow, Kubeflow, Airflow, or similar, have expertise in generative AI frameworks, containerization technologies, MLOps and LLMOps practices, and cloud-based AI services. Nice-to-have qualifications include experience with advanced GenAI applications, familiarity with experiment tracking tools, knowledge of high-performance computing techniques, and contributions to open-source MLOps or GenAI projects. In addition to technical skills, the role requires project delivery capabilities such as designing scalable deployment pipelines for ML/GenAI models, overseeing cloud infrastructure setup, and creating detailed documentation for deployment pipelines. Client engagement is another essential aspect, involving collaboration with clients to understand their business needs, presenting technical approaches and results, conducting training sessions, and creating user guides for clients. To stay ahead in the field, you will need to stay updated with the latest trends in MLOps/LLMOps and Generative AI, apply this knowledge to improve existing systems and processes, develop internal tools and frameworks, mentor junior team members, and contribute to technical publications. The ideal candidate for this position should hold any graduate/BE/B.Tech/MCA/M.Sc/M.E/M.Tech/Masters Degree/MBA. Join us at PwC and be part of a dynamic team driving innovation in data and analytics!,

As a Senior Data Scientist with 5+ years of experience, you will be responsible for designing and implementing models, mining data for insights, and interpreting complex data structures to drive business decision-making. Your expertise in machine learning, including areas such as NLP, Machine vision, and Time series, will be essential in this role. You will be expected to have strong skills in Model Tuning, Model Validation, Supervised and Unsupervised Learning, and hands-on experience with model development, data preparation, training, and inference-ready deployment of models. Your proficiency in descriptive and inferential statistics, hypothesis testing, and data analysis will help in developing code for reproducible analysis of data. Experience with AWS services like Sagemaker, Lambda, Glue, Step functions, and EC2 is necessary, along with knowledge of Databricks, Anaconda distribution, and similar data science code development and deployment IDEs. Your familiarity with ML algorithms related to time-series, natural language processing, optimization, object detection, topic modeling, clustering, and regression analysis will be highly valued. You should have expertise in Hive/Impala, Spark, Python, Pandas, Keras, SKLearn, StatsModels, Tensorflow, and PyTorch. End-to-end model deployment and production experience of at least 1 year is required, along with a good understanding of Model Deployment in Azure ML platform, Anaconda Enterprise, or AWS Sagemaker. Basic knowledge of deep learning algorithms such as MaskedCNN, YOLO, and familiarity with Visualization and analytics/Reporting Tools like Power BI, Tableau, and Alteryx will be considered advantageous for this role.,

As a Site Reliability Engineering (SRE) Technical Leader on the Network Assurance Data Platform (NADP) team at ThousandEyes, you will be responsible for ensuring the reliability, scalability, and security of cloud and big data platforms. Your role will involve representing the NADP SRE team, working in a dynamic environment, and providing technical leadership in defining and executing the team's technical roadmap. Collaborating with cross-functional teams, including software development, product management, customers, and security teams, is essential. Your contributions will directly impact the success of machine learning (ML) and AI initiatives by ensuring a robust and efficient platform infrastructure aligned with operational excellence. In this role, you will design, build, and optimize cloud and data infrastructure to ensure high availability, reliability, and scalability of big-data and ML/AI systems. Collaboration with cross-functional teams will be crucial in creating secure, scalable solutions that support ML/AI workloads and enhance operational efficiency through automation. Troubleshooting complex technical problems, conducting root cause analyses, and contributing to continuous improvement efforts are key responsibilities. You will lead the architectural vision, shape the team's technical strategy and roadmap, and act as a mentor and technical leader to foster a culture of engineering and operational excellence. Engaging with customers and stakeholders to understand use cases and feedback, translating them into actionable insights, and effectively influencing stakeholders at all levels are essential aspects of the role. Utilizing strong programming skills to integrate software and systems engineering, building core data platform capabilities and automation to meet enterprise customer needs, is a crucial requirement. Developing strategic roadmaps, processes, plans, and infrastructure to efficiently deploy new software components at an enterprise scale while enforcing engineering best practices is also part of the role. Qualifications for this position include 8-12 years of relevant experience and a bachelor's engineering degree in computer science or its equivalent. Candidates should have the ability to design and implement scalable solutions with a focus on streamlining operations. Strong hands-on experience in Cloud, preferably AWS, is required, along with Infrastructure as a Code skills, ideally with Terraform and EKS or Kubernetes. Proficiency in observability tools like Prometheus, Grafana, Thanos, CloudWatch, OpenTelemetry, and the ELK stack is necessary. Writing high-quality code in Python, Go, or equivalent programming languages is essential, as well as a good understanding of Unix/Linux systems, system libraries, file systems, and client-server protocols. Experience in building Cloud, Big data, and/or ML/AI infrastructure, architecting software and infrastructure at scale, and certifications in cloud and security domains are beneficial qualifications for this role. Cisco emphasizes diversity and encourages candidates to apply even if they do not meet every single qualification. Diverse perspectives and skills are valued, and Cisco believes that diverse teams are better equipped to solve problems, innovate, and create a positive impact.,

Join the Agentforce team in AI Cloud at Salesforce and make a real impact with your software designs and code! This position requires technical skills, outstanding analytical and influencing skills, and extraordinary business insight. It is a multi-functional role that requires building alignment and communication with several engineering organizations. We work in a highly collaborative environment, and you will partner with a highly cross-functional team comprised of Data Scientists, Software Engineers, Machine learning engineers, UX experts, and product managers to build upon Agentforce, our cutting-edge new AI framework. We value execution, clear communication, feedback, and making learning fun. Your impact - You will: Architect, design, implement, test, and deliver highly scalable AI solutions: Agents, AI Copilots/assistants, Chatbots, AI Planners, RAG solutions. Be accountable for defining and driving software architecture and enterprise capabilities (scalability, fault tolerance, extensibility, maintainability, etc.) Independently design sophisticated software systems for high-end solutions, while working in a consultative fashion with other senior engineers and architects in AI Cloud and across the company. Determine overall architectural principles, frameworks, and standards to craft vision and roadmaps. Analyze and provide feedback on product strategy and technical feasibility. Drive long-term design strategies that span multiple sophisticated projects, deliver technical reports and performance presentations to customers and at industry events. Actively communicate with, encourage, and motivate all levels of staff. Be a subject matter expert for multiple products, while writing code and working closely with other developers, PM, and UX to ensure features are delivered to meet business and quality requirements. Troubleshoot complex production issues and interface with support and customers as needed. Drive long-term design strategies that span multiple sophisticated projects, deliver technical reports and performance presentations to customers and at industry events. Required Skills: 12+ years of experience in building highly scalable Software-as-a-Service applications/platform. Experience building technical architectures that address complex performance issues. Thrive in dynamic environments, working on cutting-edge projects that often come with ambiguity. Innovation/startup mindset to be able to adapt. Deep knowledge of object-oriented programming and experience with at least one object-oriented programming language, preferably Java. Proven ability to mentor team members to support their understanding and growth of software engineering architecture concepts and aid in their technical development. High proficiency in at least one high-level programming language and web framework (NodeJS, Express, Hapi, etc.). Proven understanding of web technologies, such as JavaScript, CSS, HTML5, XML, JavaScript, JSON, and/or Ajax. Data model design, database technologies (RDBMS & NoSQL), and languages such as SQL and PL/SQL. Experience delivering or partnering with teams that ship AI products at high scale. Experience in automated testing, including unit and functional testing using Java, JUnit, JSUnit, Selenium. Demonstrated ability to drive long-term design strategies that span multiple complex projects. Experience delivering technical reports and presentations to customers and at industry events. Demonstrated track record of cultivating strong working relationships and driving collaboration across multiple technical and business teams to resolve critical issues. Experience with the full software lifecycle in highly agile and ambiguous environments. Excellent interpersonal and communication skills. Preferred Skills: Solid experience in API development, API lifecycle management, and/or client SDKs development. Experience with machine learning or cloud technology platforms like AWS sagemaker, terraform, spinnaker, EKS, GKE. Experience with AI/ML and Data science, including Predictive and Generative AI. Experience with data engineering, data pipelines, or distributed systems. Experience with continuous integration (CI) and continuous deployment (CD), and service ownership. Familiarity with Salesforce APIs and technologies. Ability to support/resolve production customer escalations with excellent debugging and problem-solving skills.,

Are you seeking an exciting opportunity to join a dynamic and fast-paced team in a challenging area Join our team as a Quantitative Research Associate in the Asset & Wealth Management Risk Team. You will play a crucial role in developing and maintaining risk measurement methodologies, performing analytics calculations, and managing the Asset and Wealth Management Risk System (Newton). Your responsibilities will include contributing to the research and enhancement of risk methodologies for AWM Risk Analytics, collaborating with peers and stakeholders to identify opportunities for Data Science, assisting in continuous improvements of Machine Learning techniques, and designing scalable solutions using approved tools. Additionally, you will prepare model documentation for Model Risk Governance and Review, analyze new data sets, and ensure adherence to best practices in data model and architecture. The ideal candidate should have 2+ years of experience in quantitative analysis, data science, or a related field, possess strong technical skills, be detail-oriented, and have excellent communication abilities. A solid understanding of statistics, AI/ML techniques, and problem-solving skills is crucial. Knowledge of asset pricing, VaR backtesting, and programming languages like SQL, Python, and familiarity with ML tools like AWS Sagemaker and TensorFlow are preferred. A degree in Economics, Mathematics/Statistics, Engineering, Computer Science, or a related field is also preferred. Join us on a journey of innovation to introduce data-driven risk analytics solutions and transform our operations through machine learning techniques to enhance our system's value proposition.,

Hi All Job Title: MLOPS Engineer Exp: 5+ Years Location: Hyderabad, Trivandrum, Kochi Mandatory Skillset - MLOps, Python, AWS, CI CD pipeline

Join us and drive the design and deployment of AI/ML frameworks revolutionizing telecom services. As a key member of our team, you will architect and build scalable, secure AI systems for service assurance, orchestration, and fulfillment, working directly with network experts to drive business impact. You will be responsible for defining architecture blueprints, selecting the right tools and platforms, and guiding cross-functional teams to deliver scalable AI systems. This role offers significant growth potential, mentorship opportunities, and the chance to shape the future of telecoms using the latest AI technologies and platforms. You have: 10+ years' experience in AI/ML design and deployment with a Graduation or equivalent degree. Practical Experience on AI/ML techniques and scalable architecture design for telecom operations, inventory management, and ETL. Exposure to data platforms (Kafka, Spark, Hadoop), model orchestration (Kubeflow, MLflow), and cloud-native deployment (AWS Sagemaker, Azure ML). Proficient in programming (Python, Java) and DevOps/MLOps best practices. It will be nice if you had: Worked with any of the LLM models (llama family) and LLM agent frameworks like LangChain / CrewAI / AutoGen Familiarity with telecom protocols, OSS/BSS platforms, 5G architecture, and NFV/SDN concepts. Excellent communication and stakeholder management skills. Key Responsibilities Design end-to-end AI architecture tailored to telecom services business functions (e.g., Service assurance, Orchestration and Fulfilment). Define data strategy and AI workflows including Inventory Model, ETL, model training, deployment, and monitoring. Evaluate and select AI platforms, tools, and frameworks suited for telecom-scale workloads for development and testing of Inventory services solutions Work closely with telecom network experts and Architects to align AI initiatives with business goals. Ensure scalability, performance, and security in AI systems across hybrid/multi-cloud environments. Mentor AI developers

About The Role Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : NoSQL Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI/ML Engineer, you will develop applications and systems utilizing AI tools, Cloud AI services, with a proper cloud or on-prem application pipeline of production-ready quality. You will apply GenAI models as part of the solution, including deep learning, neural networks, chatbots, and image processing. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Lead the implementation of AI/ML models.- Conduct research on emerging AI technologies.- Optimize AI algorithms for performance and scalability. Professional & Technical Skills: - Must To Have Skills: Proficiency in NoSQL.- Strong understanding of AI and ML concepts.- Experience with cloud AI services like AWS SageMaker or Google AI Platform.- Knowledge of deep learning frameworks such as TensorFlow or PyTorch.- Hands-on experience in developing AI applications.- Familiarity with chatbot development and image processing. Additional Information:- The candidate should have a minimum of 5 years of experience in NoSQL.- This position is based at our Bengaluru office.- A 15 years full-time education is required. Qualification 15 years full time education

About The Role Skill required: Delivery - Advanced Analytics Designation: I&F Decision Sci Practitioner Specialist Qualifications: Master of Engineering/Masters in Business Economics Years of Experience: 7 to 11 years What would you do Data & AI You will be a core member of Accenture Operations global Data & AI group, an energetic, strategic, high-visibility and high-impact team, to innovate and transform the Accenture Operations business using machine learning, advanced analytics to support data-driven decisioning. What are we looking for Extensive experience in leading Data Science and Advanced Analytics delivery teams Strong statistical programming experience Python or working knowledge on cloud native platforms like AWS Sagemaker is preferred Azure/ GCP Experience working with large data sets and big data tools like AWS, SQL, PySpark, etc. Solid knowledge in at least more than two of the following Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling (random forest, boosted tree, etc) Experience in working with Pricing models is a plus Experience in atleast one of these business domains:Energy, CPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, Supply Chain Extensive experience in client engagement and business development Ability to work in a global collaborative team environment Quick Learner and Independently deliver results. Qualifications:Masters / Ph.D. Computer science, Engineering, Statistics, Mathematics, Economics or related disciplines. Roles and Responsibilities: Building data science models to uncover deeper insights, predict future outcomes, and optimize business processes for clients. Utilizing advanced statistical and machine learning techniques to develop models that can assist in decision-making and strategic planning. Refining and improving data science models based on feedback, new data, and evolving business needs. Data Scientists in Operations follow multiple approaches for project execution from adapting existing assets to Operations use cases, exploring third-party and open-source solutions for speed to execution and for specific use cases to engaging in fundamental research to develop novel solutions. Data Scientists are expected to collaborate with other data scientists, subject matter experts, sales, and delivery teams from Accenture locations around the globe to deliver strategic advanced machine learning / data-AI solutions from design to deployment. Qualification Master of Engineering,Masters in Business Economics