7757 Machine Learning Jobs - Page 21

Project Role : BI Architect Project Role Description : Build and design scalable and open Business Intelligence (BI) architecture to provide cross-enterprise visibility and agility for business innovation. Create industry and function data models used to build reports and dashboards. Ensure the architecture and interface seamlessly integrates with Accentures Data and AI framework, meeting client needs. Must have skills : SAS Base & Macros Good to have skills : NA Minimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary: As a SAS BASE & MACROS, you will be responsible for building and designing scalable and open Business Intelligence (BI) architecture to provide cross-enterprise visibility and agility for business innovation. You will create industry and function data models used to build reports and dashboards, ensuring seamless integration with Accentures Data and AI framework to meet client needs. Roles & Responsibilities: 1.Data Engineer to lead or drive the migration of legacy SAS data preparation jobs to a modern Python-based data engineering framework. 2. Should have deep experience in both SAS and Python, strong knowledge of data transformation workflows, and a solid understanding of database systems and ETL best practices. 3.Should analyze existing SAS data preparation and data feed scripts and workflows to identify logic and dependencies. 4.Should translate and re-engineer SAS jobs into scalable, efficient Python-based data pipelines. 5.Collaborate with data analysts, scientists, and engineers to validate and test converted workflows. 6.Optimize performance of new Python workflows and ensure data quality and consistency. 7.Document migration processes, coding standards, and pipeline configurations. 8.Integrate new pipelines with google cloud platforms as required. 9.Provide guidance and support for testing, validation, and production deployment Professional & Technical Skills: - Must To Have Skills: Proficiency in SAS Base & Macros - Strong understanding of statistical analysis and machine learning algorithms - Experience with data visualization tools such as Tableau or Power BI - Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms - Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity Additional Information: - The candidate should have 8+ years of exp with min 3 years of exp in SAS or python Data engineering 15 years full time education

Skills Required 6+ years of experience in AI, Machine learning and Data Science Experience in using AI and ML services from the GCP and AWS Machine Learning, Neural Network and Data-Science using Pandas, Gensim, NLTK, Spacy, Bertopic Programming skills in Python, Python Data science, Django, AWS, Dev-Ops, Rive Script, Tableau and Kafka-Zookeeper. Relational and non-relational databases like Postgres and DynamoDB Validation & Model deployment On premise/cloud deployment

This is a full-time on-site role for an Professors | Associate Professors | Assistant Professor for School Of Computers The Teaching FACULTY will be responsible for conducting lectures, preparing course materials, grading assignments and exams, providing guidance mentoring and Skill development to students, and conducting research in their field of expertise. Responsibilities: Curriculum Development: Designing and developing undergraduate and postgraduate courses in computer science and related fields. Lecture Delivery: Delivering engaging lectures on various computer science topics, such as programming, data structures, algorithms, database systems, artificial intelligence, machine learning, and cybersecurity. Lab Sessions: Conducting practical laboratory sessions to provide hands-on experience to students. Student Guidance: Providing academic guidance and mentoring to students. Evaluation: Assessing student performance through exams, assignments, and projects. Research Responsibilities: Research Projects: Conducting independent research in their area of specialization. Publication: Publishing research papers in reputable academic journals and conferences. Grant Acquisition: Securing research grants to fund research projects. Supervision: Supervising research scholars and postgraduate students. Post Ph.D with a minimum of 0- 1 years of teaching experience in Academia / Research /Industry _

This is a full-time on-site role for an Professors | Associate Professors | Assistant Professor for School Of Computers The Teaching FACULTY will be responsible for conducting lectures, preparing course materials, grading assignments and exams, providing guidance mentoring and Skill development to students, and conducting research in their field of expertise.Responsibilities: Curriculum Development: Designing and developing undergraduate and postgraduate courses in computer science and related fields. Lecture Delivery: Delivering engaging lectures on various computer science topics, such as programming, data structures, algorithms, database systems, artificial intelligence, machine learning, and cybersecurity. Lab Sessions: Conducting practical laboratory sessions to provide hands-on experience to students. Student Guidance: Providing academic guidance and mentoring to students. Evaluation: Assessing student performance through exams, assignments, and projects. Research Responsibilities: Research Projects: Conducting independent research in their area of specialization. Publication: Publishing research papers in reputable academic journals and conferences. Grant Acquisition: Securing research grants to fund research projects. Supervision: Supervising research scholars and postgraduate students.

This is a full-time on-site role for an Professors | Associate Professors | Assistant Professor for School Of Computers The Teaching FACULTY will be responsible for conducting lectures, preparing course materials, grading assignments and exams, providing guidance mentoring and Skill development to students, and conducting research in their field of expertise.Responsibilities: Curriculum Development: Designing and developing undergraduate and postgraduate courses in computer science and related fields. Lecture Delivery: Delivering engaging lectures on various computer science topics, such as programming, data structures, algorithms, database systems, artificial intelligence, machine learning, and cybersecurity. Lab Sessions: Conducting practical laboratory sessions to provide hands-on experience to students. Student Guidance: Providing academic guidance and mentoring to students. Evaluation: Assessing student performance through exams, assignments, and projects. Research Responsibilities: Research Projects: Conducting independent research in their area of specialization. Publication: Publishing research papers in reputable academic journals and conferences. Grant Acquisition: Securing research grants to fund research projects. Supervision: Supervising research scholars and postgraduate students. Post M.Tech with a minimum of 1 years of teaching experience.

AI/ML Engineer Responsibilities: Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models. Transforming data science prototypes and applying appropriate ML algorithms and tools. Ensuring that algorithms generate accurate user recommendations. Turning unstructured data into useful information by auto-tagging images and text-to-speech conversions. Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks. Developing ML algorithms to huge volumes of historical data to make predictions. Running tests, performing statistical analysis, and interpreting test results. Documenting machine learning processes. Keeping abreast of developments in machine learning. AI/ML Engineer Requirements: Bachelor's degree in computer science, data science, mathematics, or a related field with at least 3+yrs of experience as an AI/ML Engineer Advanced proficiency with Python and FastAPI framework along with good exposure to libraries like scikit-learn, Pandas, NumPy etc.. Experience in working on ChatGPT, LangChain (Must), Large Language Models (Good to have) & Knowledge Graphs Extensive knowledge of ML frameworks, libraries, data structures, data modelling, and software architecture. In-depth knowledge of mathematics, statistics, and algorithms. Superb analytical and problem-solving abilities. Great communication and collaboration skills.

Principal Data Scientist JOB TITLE : Principal Data Scientist Technical Skill / Delivery: Ability to prepare model training data in BigQuery and GCS Strong SQL skills working with complex queries (Aggregate/ Window functions/CASE statements). Excellent scripting and coding skills, able to code using well defined patterns Strong Machine Learning modeling skills and MLOpsAble to build/deploy/support end to end (Data Ingestion/Prep – Model Training – Dashboard) machine learning systems. Expertise with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn) Query optimization to improve data preparation performance Hands on experience with Google Data and ML Products (e.g. BigQuery, VertexAI Notebooks and Pipelines, etc.). Experience in data processing using SQL and PySpark Able to build/deploy end to end (Data Ingestion/Prep – Model Training – Dashboard) machine learning systems. Ability to lead Machine Learning projects end to end (Data Ingestion – Data Prep – Model Training – Deployment – Dashboarding). Working with JIRA/Confluence. Best Practices: Strong knowledge in DevOps/MLOps best practices Experience in using multiple ML Libraries in cross platform implementations (Python/R) Experience in Machine Learning Training/Prediction/Deployment implementation. Business Domain: Good understanding of internal data domains (e.g. Empower, Oracle, Kronos, Employee, NICE). Good understanding of Contact Center Switch data Soft Skills Ability to write clear concise code. Strong organizational skills. Able to work with cross functional teams in problem solving and adding business value with AI-ML. Strong team player. Good verbal & written communication skills Must be a fast learner Ability to document processes in the Machine Learning Lifecycle Strong team player by contributing to the innovative ideas that enhance our AI-ML capabilities. Strong documentation skills. Build strong relationship with business partners. About TTEC Our business is about making customers happy. That's all we do. Since 1982, we've helped companies build engaged, pleased, profitable customer experiences powered by our combination of humanity and technology. On behalf of many of the world's leading iconic and hypergrowth brands, we talk, message, text, and video chat with millions of customers every day. These exceptional customer experiences start with you. TTEC is proud to be an equal opportunity employer where all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. TTEC embraces and is committed to building a diverse and inclusive workforce that respects and empowers the cultures and perspectives within our global teams. We aim to reflect the communities we serve, by not only delivering amazing service and technology, but also humanity. We make it a point to make sure all our employees feel valued, belonging, and comfortable being their authentic selves at work. As a global company, we know diversity is our strength because it enables us to view things from different vantage points and for you to bring value to the table in your own unique way. Primary Location : India-Telangana-Hyderabad

The Digital :Google Data Engineering E2 role involves working with relevant technologies, ensuring smooth operations, and contributing to business objectives. Responsibilities include analysis, development, implementation, and troubleshooting within the Digital :Google Data Engineering E2 domain.

We are seeking a dynamic and motivated MBA graduate to support our transformation office. This is a unique opportunity to gain hands-on experience in strategic transformation initiatives, working closely with cross-functional teams and senior stakeholders. Key Responsibilities: Support Strategic Transformation Initiatives Assist in aligning transformation activities with business goals, focusing on process improvement, automation, AI integration, and data-driven insights. Facilitate Idea Generation Workshops Help organize and document sessions using design thinking, process mining, and benchmarking to surface impactful transformation opportunities. Developing new Strategy / Consulting offerings for Digital Transformation, Innovation and implementation Assist in Business Case Development Collaborate with senior team members to prepare business cases, including ROI estimates, cost-benefit analysis, and strategic value assessments. Contribute to Commercial Strategy Support the development of pricing models and commercial frameworks for digital and automation-led services. Change Management Support Help coordinate change management efforts, including communication plans, stakeholder engagement, and adoption tracking. Monitor Value Realization Track KPIs and assist in reporting the impact of transformation initiatives on cost, revenue, and business outcomes. Drive Transformation Council Activities Promote Innovation Culture Assist in organizing training sessions, knowledge-sharing forums, and recognition programs to foster continuous improvement. Preferred candidate profile Recent MBA graduate with a strong interest in business transformation, strategy, or operations. Excellent analytical, communication, and collaboration skills. Eagerness to learn and contribute in a fast-paced, evolving environment. Proficiency in AI Co-pilot, basic data analysis tools.

About the Role As a GenAI MLOps Engineer on our AI Engineering team, youll build, deploy, and maintain the core infrastructure that powers our generative-AI products. Youll partner closely with data scientists and software engineers to productionize LLM-based models, automate workflows, and keep services reliable and cost-effective. Core Responsibilities (Must-Have) Pipeline & CI/CD Design, build, and operate repeatable ML pipelines (data prep training evaluation deploy) using tools such as Airflow, Prefect, or cloud-native solutions. Author automated CI/CD workflows (GitHub Actions, Azure DevOps, or Jenkins) for model code, pipelines, and container builds, including linting and automated tests. Model Deployment & Serving Containerize models with Docker; deploy to Kubernetes (AKS/EKS/GKE) or serverless (Cloud Run, Azure Functions). Implement safe rollout patterns (canary, blue/green) to minimize risk when updating model versions. Monitoring & Alerting Instrument inference endpoints and pipelines with key metrics (latency, throughput) and logs. Create dashboards and alerts (Prometheus/Grafana or cloud-native alternatives) to detect errors, drift, and performance regressions. Cloud & Infrastructure Operate core compute resources on one major cloud platform (Azure Databricks, AWS SageMaker, or GCP Vertex AI). Write and maintain basic Infrastructure-as-Code (Terraform, or CloudFormation) for provisioning clusters and managed services. GenAI Orchestration & Vector Retrieval Use orchestration framework (e.g., LangGraph, Langfuse etc) to automate GenAI workflows. Support embedding-based retrieval pipelines: collaborate on vector index maintenance and refresh processes. Collaboration & Documentation Work with data science to integrate new models into production. Produce clear runbooks, architecture diagrams, and “on-call” guides. Qualifications 5 years in DevOps/MLOps roles, including at least 3 years supporting ML or deep-learning systems. Hands-on with one major cloud (Azure/AWS/GCP) and experience provisioning compute for training/inference. Strong skills in Docker and Kubernetes or serverless deployments. Proven ability to author CI/CD pipelines and IaC. Experience with monitoring stacks (Prometheus/Grafana, Datadog, or cloud-native tools). Familiarity with a prompt-orchestration framework (e.g., LangChain) and core vector-retrieval concepts. Soft Skills Effective communicator who can translate technical details to cross-functional teams. Strong problem-solver who can troubleshoot across data, model, and infrastructure layers. Eager to learn new tools and iterate rapidly in a fast-paced environment. Additional Information Growth & Nice-to-Have Security & Compliance: Basic API auth (OAuth/JWT), secrets management (Key Vault, AWS KMS), and data encryption. Testing & Validation: Data-quality checks (e.g., Great Expectations), adversarial testing, and automated model-quality gates. Scalability & Cost Optimization: Capacity planning, load testing (Locust, JMeter), spot-instance usage, and caching strategies (Redis). Reliability Engineering: Participation in on-call rotations, post-mortems, and error-budget SLOs; chaos-testing fundamentals. Experimentation Lifecycle: Tracking experiments and hyperparameter sweeps (MLflow, Optuna), and supporting A/B tests. Tooling Flexibility: Familiarity with alternative MLOps frameworks (Kubeflow, TFX) or observability stacks (OpenTelemetry). Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP)

Data Science Trainer Codegnan IT Solutions Pvt Ltd **Location:** Hyderabad and Vijayawada Job Responsibilities: Deliver high-quality training sessions on Data Science, Machine Learning, and related topics. Prepare course materials, assignments, and projects for students. Assess student performance and provide feedback. Stay updated with the latest trends in Data Science and incorporate them into training modules. Support students in their learning journey with doubt clarification and project guidance. Required Qualifications & Skills: Bachelor's or Master’s degree in Computer Science, Data Science or related field. Strong knowledge of Python, statistics, machine learning algorithms, and data visualization tools. Prior teaching or training experience preferred. Excellent communication and presentation skills. Hands-on experience with tools like Jupyter, Pandas, NumPy, Scikit-learn, TensorFlow, etc.

Role & responsibilities Skill - AI/ML python Engineer Exp - 5+ Location - Gurgaon Notice period - Immediate joiners We are hiring a senior Software Engineer with 5+ years of strong experience in Python development and a solid foundation in AI/ML concepts and practical implementation. The role requires hands-on work with Generative AI libraries and Large Language Models (LLMs), along with a good understanding of the machine learning lifecycle. Experience with AWS cloud services is preferred. Key Responsibilities: Develop AI/ML applications using Python with a focus on Generative AI. Work with libraries like OpenAI, Hugging Face Transformers, and related GenAI tools. Apply concepts related to Large Language Models (LLMs) such as GPT, Claude, etc. Build and manage ML workflows including data preprocessing, model training, evaluation, and deployment. Collaborate with cross-functional teams to integrate AI features into scalable solutions. Required Skills: Strong Python development experience with a focus on AI/ML. Hands-on experience with GenAI libraries like OpenAI, Hugging Face Transformers, etc. Understanding and practical knowledge of LLMs (e.g., GPT, Claude) and associated concepts. Familiarity with the ML lifecycle preprocessing, training, evaluation, and deployment. Preferred: Experience working with AWS cloud platform and its services.

Job purpose: Design, develop, and deploy end-to-end AI/ML systems, focusing on large language models (LLMs), prompt engineering, and scalable system architecture. Leverage technologies such as Java/Node.js/NET to build robust, high-performance solutions that integrate with enterprise systems. Who You Are: Education: Bachelors or Masters degree in Computer Science, Engineering, or a related field. PhD is a plus. 5+ years of experience in AI/ML development, with at least 2 years working on LLMs or NLP. Proven expertise in end-to-end system design and deployment of production-grade AI systems. Hands-on experience with Java/Node.js/.NET for backend development. Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Hugging Face Transformers). Key Responsibilities: 1. Model Development & Training: Design, train, and fine-tune large language models (LLMs) for tasks such as natural language understanding, generation, and classification. Implement and optimize machine learning algorithms using frameworks like TensorFlow, PyTorch, or Hugging Face. 2. Prompt Engineering: Craft high-quality prompts to maximize LLM performance for specific use cases, including chatbots, text summarization, and question-answering systems. Experiment with prompt tuning and few-shot learning techniques to improve model accuracy and efficiency. 3. End-to-End System Design: Architect scalable, secure, and fault-tolerant AI/ML systems, integrating LLMs with backend services and APIs. Develop microservices-based architectures using Java/Node.js/.NET for seamless integration with enterprise applications. Design and implement data pipelines for preprocessing, feature engineering, and model inference. 4. Integration & Deployment: Deploy ML models and LLMs to production environments using containerization (Docker, Kubernetes) and cloud platforms (AWS/Azure/GCP). Build RESTful or GraphQL APIs to expose AI capabilities to front-end or third-party applications. 5. Performance Optimization: Optimize LLMs for latency, throughput, and resource efficiency using techniques like quantization, pruning, and model distillation. Monitor and improve system performance through logging, metrics, and A/B testing. 6. Collaboration & Leadership: Work closely with data scientists, software engineers, and product managers to align AI solutions with business objectives. Mentor junior engineers and contribute to best practices for AI/ML development. What will excite us: Strong understanding of LLM architectures and prompt engineering techniques. Experience with backend development using Java/Node.js (Express)/.NET Core. Familiarity with cloud platforms (AWS, Azure, GCP) and DevOps tools (Docker, Kubernetes, CI/CD). Knowledge of database systems (SQL, NoSQL) and data pipeline tools (Apache Kafka, Airflow). Strong problem-solving and analytical skills. Excellent communication and teamwork abilities. Ability to work in a fast-paced, collaborative environment. What will excite you: Lead AI innovation in a fast-growing, technology-driven organization. Work on cutting-edge AI solutions, including LLMs, autonomous AI agents, and Generative AI applications. Engage with top-tier enterprise clients and drive AI transformation at scale. Location: Ahmedabad

About the Role We are looking for a highly skilled and motivated AI ML Engineer with a strong background in LLMs, RAG pipelines, MLOps, and Azure Cloud . The ideal candidate should have deep experience in building and fine-tuning LLMs, deploying ML systems at scale, and integrating AI capabilities into enterprise-grade applications. Key Responsibilities Design and implement RAG (Retrieval-Augmented Generation) pipelines and AI agentic systems using LLM frameworks. Fine-tune LLMs and develop narrow, domain-specific models using industry best practices. Collaborate with data scientists and product teams to deploy ML models in production environments. Build and maintain robust MLOps pipelines using MLFlow , ensuring reproducibility and traceability of experiments. Integrate and deploy solutions using Azure DevOps and related cloud services. Implement secure and scalable authentication flows using Azure AD and GraphAPI . Optimize performance of deployed models with a focus on latency, cost, and maintainability. Document and present architecture, experiment results, and production workflows. Required Skills & Experience Strong foundational knowledge in Computer Science, IT systems, and architecture . Proficient in Python , with solid experience in both Object-Oriented and Functional Programming paradigms . Practical experience with LLMs , including open-source models. Hands-on experience with RAG pipelines and AI agentic frameworks . Expertise in MLOps tooling , especially MLFlow , model versioning, and CI/CD for ML. Solid understanding of model deployment and serving using Docker, Kubernetes, FastAPI, etc. Proven experience working with Azure cloud , including: Azure DevOps for pipelines and release management. Azure GraphAPI for organizational data access. Authentication and security protocols . Good communication skills and ability to work in cross-functional teams.

Location: Hyderabad, India | Employment Type: Full-Time Experience Level: 2+Years Company: Covasant Contact Person: Ranjith Reddy 9703455109 | ranjith.palle@covasant.cm | linkedin.com/in/ranjith-r-75a766227 Build the Future of AI with Covasant At Covasant , we don't just work with AI we engineer the next era of it. We're hiring mid-level to senior developers and AI leads to help us build next-generation agentic AI systems that are intelligent, collaborative, and scalable. This is your chance to go beyond prompt engineering and shape the architecture of autonomous, multi-agent AI solutions using tools like LangGraph, AutoGen, CrewAI , and more. If youve got the skills and curiosity to work on what the AI world will be talking about next year , we want to hear from you. Your Role Design and develop multi-agent LLM systems using LangGraph, AutoGen, or CrewAI. Build and deploy MCP servers , LLM gateways , and design Agent-to-Agent collaboration flows. Fine-tune language models for verticals like healthcare, manufacturing, or finance. Architect retrieval-augmented generation (RAG) systems with vector stores like FAISS, Pinecone, or Weaviate. Integrate tools like LangSmith , GuardrailsAI , and knowledge graphs to ensure trust, safety, and observability. Collaborate cross-functionally with product, data science, and engineering teams. What You Bring 2+ years in software development, with strong Python skills. Proven expertise in one or more: LangGraph , AutoGen , CrewAI . Deep understanding of Agent-based AI , LLM orchestration , and RAG pipelines . Experience fine-tuning LLMs and applying prompt engineering and domain adaptation . Familiarity with tools like LangSmith , PromptGuard , or Guardrails frameworks. Bonus If You Have Cloud experience (AWS, Azure, GCP) Familiarity with Docker, Kubernetes Exposure to multi-modal models (LLaMA, Mistral, Falcon) Frontend tech: React, Angular, or Vue CI/CD, MLOps, or LLMOps knowledge Important We’re currently hiring mid-level, senior, and lead professionals with hands-on experience in AI/ML projects . These openings are not for freshers or professionals with less than 2 years of experience — but we are planning something exciting for early-career AI talent soon! Why Join Covasant Work on real-world agentic AI systems ahead of industry trends Collaborative and innovation-first work culture Competitive pay, benefits & performance incentives Hybrid/flexible work setup A chance to lead and influence the next chapter in AI Let’s Connect If this excites you — whether or not you're actively job hunting — don’t miss the chance to explore this game-changing opportunity. Ranjith Reddy – 9703455109 ranjith.palle@covasant.cm Connect with me on LinkedIn – I’d love to stay in touch, even if this isn’t the right time. Apply now or just start a conversation. The future of AI doesn’t wait — and neither should you.

Only Mumbai Candidates are preferred. JD Requirement Gathering And Analysis - Document and Analyse business requirement from various stakeholders. Solution Design - Design and Configure salesforce solutions based on business needs. Ensuring alignment with organisation goals. Process optimisation - Identify and design workflows to improve business process and automation within salesforce and associated tools Documentation and Colloboration - Working closely with support and development team to ensure successful implementation and adoption Testing and Training - Participate in UATs with stakeholders and ensuring right trainings given to new/ existing users Solution implementation and data management - Ensuring implementation and scalability keeping budgets control and ensuring the data accuracy, and integrity Reporting - Using salesforce reporting and analytics for tracking performance Experience: 4-5 Years of experience in Similar role preferably for Construction/ Real estate domain Technical Skills: Strong knowledge of Data analysis and Modeling, Statistical analysis skills, Python or R with Machine Learning Skills, Data visualization

Responsibilities - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Required Skills - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Skills - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Responsibilities - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Required Skills - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Skills - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Role Purpose The purpose of this role is to develop minimum viable product (MVP) and comprehensive AI solutions that meet and exceed clients expectations and add value to business. Strong in python programming / Python Developer & hands on expertise, Advance python (OOPS), strong in MySQL/SQL. Python API OR Flask OR Django Framework. ROLE / RESPONSIBILITIES Develop a thorough understanding of our entire technology stack Design and develop new features within existing Python services; create new services to expand the overall framework. Contribute to future design and architecture. Plan work in an agile manner with other team members Write acceptance tests in coordination with QA Provide L3 user support. Communicate with our business and platform partners. Improve and develop our CI pipeline and deployment strategies

Role Purpose The purpose of the role is to create exceptional and detailed architectural application design and provide thought leadership and enable delivery teams to provide exceptional client engagement and satisfaction. Do 1. Develop architectural application for the new deals/ major change requests in existing deals a. Creates an enterprise-wide architecture that ensures systems are scalable, reliable, and manageable. b. Manages application assets and directs the development efforts within an enterprise to improve solution delivery and agility c. Guides how to construct and assemble application components and services to support solution architecture and application development d. Maintains the frameworks and artefacts used in the implementation of an application, with reference to the systematic architecture of the overall application portfolio e. Responsible for application architecture paradigms such as service-oriented architecture (SOA) and, more specifically, microservices, ensuring business achieve agility and scalability for a faster time to market f. Provide solution of RFPs received from clients and ensure overall design assurance Develop a direction to manage the portfolio of to-be-solutions including systems, shared infrastructure services, applications in order to better match business outcome objectives Analyse technology environment, enterprise specifics, client requirements to set a collaboration design framework/ architecture Depending on the clients need with particular standards and technology stacks create complete RFPs Provide technical leadership to the design, development and implementation of custom solutions through thoughtful use of modern technology Define and understand current state solutions and identify improvements, options & tradeoffs to define target state solutions Clearly articulate and sell architectural targets, recommendations and reusable patterns and accordingly propose investment roadmaps Evaluate and recommend solutions to integrate with overall technology ecosystem Tracks industry and application trends and relates these to planning current and future IT needs g. Provides technical and strategic inputs during the project planning phase in the form of technical architectural designs and recommendations h. Account mining to find opportunities in the existing clients i. Collaborates with all relevant parties in order to review the objectives and constraints of solutions and determine conformance with the Enterprise Architecture. j. Identifies implementation risks and potential impacts. k. Create new revenue streams within applications as APIs that can be leveraged by clients l. Bring knowledge of automation in application by embracing Agile and dev-ops principles to reduce manual part 2.Understanding application requirements and design a standardize application a. Creating Intellectual Property in forms of services, patterns, models and organizational approaches b. Designing patterns, best practices and reusable applications that can be used for future references c. Ensure system capabilities are consumed by system components and set criteria for evaluating technical and business value in terms of Tolerate, Invest, Migrate and Eliminate d. Provide platform to create standardize tools, uniform design and techniques are maintained to reduce costs of maintenance e. Coordinating input on risks, costs and opportunities for concepts f. Developing customised applications for the customers aligned with their needs g. Perform design and code reviews thoroughly on regular basis, keeping in mind the security measures h. Understanding design and production procedures and standards to create prototypes and finished products i. Work closely with systems analysts, software developers, data managers and other team members to ensure successful production of application software j. Offer viable solutions for various systems and architectures to different types of businesses k. Seamless integration of new and existing systems to eliminate potential problems and maintain data structure and bring value in terms of development l. Transforming all applications into digital form and implement and evolve around mesh app and service architecture that support new technologies like IOT, blockchain, machine learning, automation, BOTS etc m.Cloud Transformation(Migration) Understanding non-functional requirements Producing artefacts such as deployment architecture, interface catalogue Identify internal and external dependency, vendor and internal IT management Support build and testing team n.Cloud Transformation(Modernization) Understanding and Defining target architecture in Integration space Assessing project pipeline / demand and align to target architecture Technical support of delivery team in terms and POC and technical guidance o.Keep Up-to-date with the latest technologies in the market Mandatory Skills: Fullstack Java Enterprise. Experience8-10 Years.

Must-have skills: Global Supply Chain Management (SCM) Good to have skills: Knowledge of emerging technologies, cloud computing, and cybersecurity best practices. Job Summary : Candidate should have good understanding of statistics/analytical/optimization methods and approaches. The ideal candidate should be able to bring in meaningful data driven insights supporting with statistical concepts and apply the same in wider Supply Chain area. The candidate is expected to use data science skills to solve clients business problem in the supply chain area. The candidate should have functional skill set and Supply Chain domain knowledge with ability to apply data science skill set to solve supply chain problems. Additionally, the role would require contributing towards asset development initiatives. Roles & Responsibilities: Develop and execute technology transformation strategies, oversee implementation projects, and optimize digital capabilities for business efficiency. Professional & Technical Skills: - Relevant experience in the required domain.- Strong analytical, problem-solving, and communication skills.- Ability to work in a fast-paced, dynamic environment.Experience and Education5-6 years of experience in Machine Learning and/or Optimization Techniques. Masters degree in technology or engineering or quantitative field (e.g. MSc in Statistics and Operations Research, M Tech in Industrial Engineering, Applied Math/Statistics, Computer Science) Certifications in any one or two of the areas will be an added advantage:Python, AI/ML, Optimization, Simulation, any of the cloud platforms (Azure/ GCP/ AWS). Good to haveExperience on Simulation and Optimization Visualization packages like Tableau/ Power BI Exposure to tools like BY/ Anaplan/ o9/ Kinaxis /SAP IBP Exposure to Client interaction Exposure to business platforms (o9/Kinaxis/BY) Additional Information: - Opportunity to work on innovative projects.- Career growth and leadership exposure. Qualification Experience: 8-10Years Educational Qualification: Any Degree

Role Purpose The purpose of the role is to create exceptional and detailed architectural application design and provide thought leadership and enable delivery teams to provide exceptional client engagement and satisfaction. Do 1. Develop architectural application for the new deals/ major change requests in existing deals a. Creates an enterprise-wide architecture that ensures systems are scalable, reliable, and manageable. b. Manages application assets and directs the development efforts within an enterprise to improve solution delivery and agility c. Guides how to construct and assemble application components and services to support solution architecture and application development d. Maintains the frameworks and artefacts used in the implementation of an application, with reference to the systematic architecture of the overall application portfolio e. Responsible for application architecture paradigms such as service-oriented architecture (SOA) and, more specifically, microservices, ensuring business achieve agility and scalability for a faster time to market f. Provide solution of RFPs received from clients and ensure overall design assurance Develop a direction to manage the portfolio of to-be-solutions including systems, shared infrastructure services, applications in order to better match business outcome objectives Analyse technology environment, enterprise specifics, client requirements to set a collaboration design framework/ architecture Depending on the clients need with particular standards and technology stacks create complete RFPs Provide technical leadership to the design, development and implementation of custom solutions through thoughtful use of modern technology Define and understand current state solutions and identify improvements, options & tradeoffs to define target state solutions Clearly articulate and sell architectural targets, recommendations and reusable patterns and accordingly propose investment roadmaps Evaluate and recommend solutions to integrate with overall technology ecosystem Tracks industry and application trends and relates these to planning current and future IT needs g. Provides technical and strategic inputs during the project planning phase in the form of technical architectural designs and recommendations h. Account mining to find opportunities in the existing clients i. Collaborates with all relevant parties in order to review the objectives and constraints of solutions and determine conformance with the Enterprise Architecture. j. Identifies implementation risks and potential impacts. k. Create new revenue streams within applications as APIs that can be leveraged by clients l. Bring knowledge of automation in application by embracing Agile and dev-ops principles to reduce manual part 2.Understanding application requirements and design a standardize application a. Creating Intellectual Property in forms of services, patterns, models and organizational approaches b. Designing patterns, best practices and reusable applications that can be used for future references c. Ensure system capabilities are consumed by system components and set criteria for evaluating technical and business value in terms of Tolerate, Invest, Migrate and Eliminate d. Provide platform to create standardize tools, uniform design and techniques are maintained to reduce costs of maintenance e. Coordinating input on risks, costs and opportunities for concepts f. Developing customised applications for the customers aligned with their needs g. Perform design and code reviews thoroughly on regular basis, keeping in mind the security measures h. Understanding design and production procedures and standards to create prototypes and finished products i. Work closely with systems analysts, software developers, data managers and other team members to ensure successful production of application software j. Offer viable solutions for various systems and architectures to different types of businesses k. Seamless integration of new and existing systems to eliminate potential problems and maintain data structure and bring value in terms of development l. Transforming all applications into digital form and implement and evolve around mesh app and service architecture that support new technologies like IOT, blockchain, machine learning, automation, BOTS etc m.Cloud Transformation(Migration) Understanding non-functional requirements Producing artefacts such as deployment architecture, interface catalogue Identify internal and external dependency, vendor and internal IT management Support build and testing team n.Cloud Transformation(Modernization) Understanding and Defining target architecture in Integration space Assessing project pipeline / demand and align to target architecture Technical support of delivery team in terms and POC and technical guidance o.Keep Up-to-date with the latest technologies in the market

Role Purpose The purpose of the role is to define, architect and lead delivery of machine learning and AI solutions Do 1. Demand generation through support in Solution development a. Support Go-To-Market strategy i. Collaborate with sales, pre-sales &consulting team to assist in creating solutions and propositions for proactive demand generation ii. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for recruitment, joint research initiatives and provide data science courses 2. Revenue generation through Building & operationalizing Machine Learning, Deep Learning solutions a. Develop Machine Learning / Deep learning models for decision augmentation or for automation solutions b. Collaborate with ML Engineers, Data engineers and IT to evaluate ML deployment options c. Integrate model performance management tools into the current business infrastructure 3. Team Management a. Resourcing i. Support recruitment process to on-board right resources for the team b. Talent Management i. Support on boarding and training for the team members to enhance capability & effectiveness ii. Manage team attrition c. Performance Management i. Conduct timely performance reviews and provide constructive feedback to own direct reports ii. Be a role model to team for five habits iii. Ensure that the Performance Nxt is followed for the entire team d. Employee Satisfaction and Engagement i. Lead and drive engagement initiatives for the team Deliver No. Performance Parameter Measure 1. Demand generation Order booking 2. Revenue generation through delivery Timeliness, customer success stories, customer use cases 3. Capability Building & Team Management % trained on new skills, Team attrition % Mandatory Skills: AI Cognitive. Experience5-8 Years.

Role Purpose The purpose of the role is to create exceptional and detailed architectural application design and provide thought leadership and enable delivery teams to provide exceptional client engagement and satisfaction. Do 1. Develop architectural application for the new deals/ major change requests in existing deals a. Creates an enterprise-wide architecture that ensures systems are scalable, reliable, and manageable. b. Manages application assets and directs the development efforts within an enterprise to improve solution delivery and agility c. Guides how to construct and assemble application components and services to support solution architecture and application development d. Maintains the frameworks and artefacts used in the implementation of an application, with reference to the systematic architecture of the overall application portfolio e. Responsible for application architecture paradigms such as service-oriented architecture (SOA) and, more specifically, microservices, ensuring business achieve agility and scalability for a faster time to market f. Provide solution of RFPs received from clients and ensure overall design assurance Develop a direction to manage the portfolio of to-be-solutions including systems, shared infrastructure services, applications in order to better match business outcome objectives Analyse technology environment, enterprise specifics, client requirements to set a collaboration design framework/ architecture Depending on the clients need with particular standards and technology stacks create complete RFPs Provide technical leadership to the design, development and implementation of custom solutions through thoughtful use of modern technology Define and understand current state solutions and identify improvements, options & tradeoffs to define target state solutions Clearly articulate and sell architectural targets, recommendations and reusable patterns and accordingly propose investment roadmaps Evaluate and recommend solutions to integrate with overall technology ecosystem Tracks industry and application trends and relates these to planning current and future IT needs g. Provides technical and strategic inputs during the project planning phase in the form of technical architectural designs and recommendations h. Account mining to find opportunities in the existing clients i. Collaborates with all relevant parties in order to review the objectives and constraints of solutions and determine conformance with the Enterprise Architecture. j. Identifies implementation risks and potential impacts. k. Create new revenue streams within applications as APIs that can be leveraged by clients l. Bring knowledge of automation in application by embracing Agile and dev-ops principles to reduce manual part 2.Understanding application requirements and design a standardize application a. Creating Intellectual Property in forms of services, patterns, models and organizational approaches b. Designing patterns, best practices and reusable applications that can be used for future references c. Ensure system capabilities are consumed by system components and set criteria for evaluating technical and business value in terms of Tolerate, Invest, Migrate and Eliminate d. Provide platform to create standardize tools, uniform design and techniques are maintained to reduce costs of maintenance e. Coordinating input on risks, costs and opportunities for concepts f. Developing customised applications for the customers aligned with their needs g. Perform design and code reviews thoroughly on regular basis, keeping in mind the security measures h. Understanding design and production procedures and standards to create prototypes and finished products i. Work closely with systems analysts, software developers, data managers and other team members to ensure successful production of application software j. Offer viable solutions for various systems and architectures to different types of businesses k. Seamless integration of new and existing systems to eliminate potential problems and maintain data structure and bring value in terms of development l. Transforming all applications into digital form and implement and evolve around mesh app and service architecture that support new technologies like IOT, blockchain, machine learning, automation, BOTS etc m.Cloud Transformation(Migration) Understanding non-functional requirements Producing artefacts such as deployment architecture, interface catalogue Identify internal and external dependency, vendor and internal IT management Support build and testing team n.Cloud Transformation(Modernization) Understanding and Defining target architecture in Integration space Assessing project pipeline / demand and align to target architecture Technical support of delivery team in terms and POC and technical guidance o.Keep Up-to-date with the latest technologies in the market Mandatory Skills: App-Cloud-Google. Experience>10 YEARS.

Job Role &Responsibility/Designation Quality and Process Excellence Consultant Delivery Process/ FunctionName Quality Educational Qualification B.Sc. / BE / B Tech/ MBA/ B.Stat Skills ( Must Have) Problem solving tools/ analytical skills Excellent communication / interpersonal, facilitation skills High energy level, confident, assertive and team player Experience ( Minimum) Functional knowledge of Six Sigma, Statistical tools, Quality & Process re-engineering Exposure to ISO, CMMi or COPC will be added advantage Consulting experience in Shared Services Set up/BPO space is desirable Mandatory Skills: Process Mining. Experience8-10 Years.