58 Ml Deployment Jobs - Page 2

Responsibilities: * Design, develop, test & maintain full-stack applications using Python, React.JS, Node.JS, NestJS, TypeScript & NextJS with REST APIs on AWS/Azure/GCP cloud platforms. Annual bonus

Dun & Bradstreet Technology and Corporate Services India LLP is looking for candidates for the role of Senior Analyst to support the Data Science team. The candidate needs to work closely with the team based in India and across a range of Analytics leaders who are located globally to fulfill the deliverables on a timely basis. Role & responsibilities Work across range of Analytical Solutions that includes Implementation, Testing, Validation, Documentation, Monitoring and Reporting. Extracting large data from various data sources using multiple tools such as Python/ Pyspark /Hadoop/ SQL/ etc., to perform multiple analysis. Creating data pipelines, performing model scoring, and validating model results. Utilize custom built automated frameworks for all deliverables. Work on MLOps frameworks to deploy, monitor and validate ML models in real time. Work with multiple teams such as Data Supply, ML Engineers, Technology to implement analytical solutions and models. Preferred candidate profile: 2 to 4 years of relevant experience in Data Analytics / Data Science roles. Strong programming skill in tools such as Pyspark, Python, SQL to manipulate data and create deployable production code. Knowledge of Python packages and tools. Sound Knowledge and exposure to application of Statistical / Machine Learning Techniques. Experience in building and optimizing data pipelines, architectures and data sets. Ability to interpret and translate data into meaningful business insights. Excellent verbal, written communication and presentation skills.

Responsibilities: * Design, develop, test & maintain full-stack applications using Python, React.JS, Node.JS, NestJS, TypeScript & NextJS with REST APIs on AWS/Azure/GCP cloud platforms. Annual bonus

We're hiring experienced professionals in our growing Data science Practice at EY GDS Hyderabad Office . We are looking for talented professionals to join our team. Below are the details for the open positions: Position : AI and DATA -ML Ops Engineers Experience : 4-12 years Location : Hyderabad Programming Languages: Proficiency in Python (3.x) and SQL. ML Frameworks & Libraries: Extensive knowledge of ML frameworks (TensorFlow, PyTorch, Scikit-learn), data structures, data modelling, and software architecture. Databases: Experience with SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra, DynamoDB) databases. Mathematics & Algorithms: Strong understanding of mathematics, statistics, and algorithms for machine learning applications. ML Modules & REST API: Experience in developing and integrating ML modules with RESTful APIs. Version Control: Hands-on experience with Git and best practices for version control. Model Deployment & Monitoring: Experience in deploying and monitoring ML models using: MLflow (for model tracking, versioning, and deployment) WhyLabs (for model monitoring and data drift detection) Kubeflow (for orchestrating ML workflows) Airflow (for managing ML pipelines) Docker & Kubernetes (for containerization and orchestration) Prometheus & Grafana (for logging and real-time monitoring) Data Processing: Ability to process and transform unstructured data into meaningful insights (e.g., auto-tagging images, text-to-speech conversions) Apply Here: https://careers.ey.com/job-invite/1606302/ Please share the updated resume to Gayathri.s8@gds.ey.com . We look forward to discussing your potential with EY!

Greetings from Peoplefy Infosolutions !!! We are hiring for one of our reputed MNC client based in Pune . We are looking for candidates with 7 + years of experience in below skills - Primary skills : Cloud -google cloud preferred but cloud any will do ML deployment using Jenkins/Harness Python Kubernetes terraform Interested candidates for above position kindly share your CVs on sayali.va@peoplefy.com with below details - Experience : CTC : Expected CTC : Notice Period : Location :

About Aplazo Aplazo is a Mexican BNPL startup redefining financial access for the underbanked. Unlike its global counterparts, Aplazo isnt just about debtits an alternative to cash, offering fair, simple, and transparent financial solutions. Founded four years ago, Aplazo enables users to split payments online and in-store without a credit card, empowering financial freedom and opportunity across Latin America. Our tech-driven approach minimizes credit loss while ensuring accessibility—even for the 40% of users with no credit history. With in-store transactions making up more than half of our business, we bridge the gap in Mexico’s evolving financial landscape. Merchants benefit from increased basket sizes, higher conversions, and stronger customer engagement. Backed by $110M in funding , Aplazo is poised for continued innovation. We’re building Latin America’s most beloved fintech and are seeking passionate technologists and leaders who thrive on collaboration, quality, and impact . Aplazo on TechCrunch : https://techcrunch.com/2024/05/13/aplazo/ About Data Science @ Aplazo The Data Science team at Aplazo is a strategic driver of innovation and transformation. With a strong product-first mindset and deep technical expertise, we solve complex problems across risk, payments, personalization, fraud detection, marketing, customer lifecycle, recommendations, underwriting, and more. A cornerstone of our success is our robust MLOps infrastructure —featuring automated CI/CD pipelines, model and data versioning, and comprehensive observability to support a seamless end-to-end ML lifecycle. Now, we are investing in next-generation MLOps capabilities to further scale and future-proof our systems. Role Overview We are seeking a visionary Lead/Staff MLOps Engineer to lead the evolution of our ML infrastructure. This is a high-impact role for a technical leader who thrives on building scalable platforms, accelerating experimentation workflows, and enabling high-velocity AI development. You’ll define the MLOps roadmap, establish best practices, and build resilient systems that empower our Data Science and Engineering teams to operate at scale. You will work closely with stakeholders across Product, Growth, Engineering, and Data to translate complex business goals into reliable, high-performing machine learning systems. Key Responsibilities Architect scalable ML systems with a focus on reliability, security, automation, and performance Lead the end-to-end MLOps strategy : CI/CD for ML, model registries, feature stores, testing, deployment, and monitoring Drive innovation across ML domains (LLMs, NLP, personalization, fraud detection, pricing, customer science) Optimize ML workflows for cost, latency, reproducibility , and resource efficiency Define rigorous model governance standards including auditability, reproducibility, versioning, rollback mechanisms Evaluate and integrate new technologies (LLMOps, Foundation Models, LangChain, etc.) through structured POCs Serve as technical mentor and thought leader , influencing teams and instilling engineering excellence Partner with executive leadership on quarterly OKRs aligned to risk-adjusted growth, profitability, and model performance Collaborate across geographies—Mexico, USA, Chile, and Europe—to ensure strategic alignment Required Qualifications Experience 6+ years in MLOps, ML Engineering, or Software Engineering, with 2+ years in a senior leadership role Proven success in building and scaling production-grade ML platforms Strong exposure to cloud-native infrastructure (GCP or AWS preferred) Experience deploying AI/GenAI systems in regulated environments Technical Skills Expert in Python and ML stack (TensorFlow, PyTorch, Scikit-learn, LangChain, OpenAI APIs) CI/CD tools (GitHub Actions, Argo, Kubeflow, MLflow) Kubernetes, Docker, ONNX, TorchServe for model serving and orchestration Strong with data warehousing and processing tools (BigQuery, Snowflake, Spark, Kafka, Flink) Experience with metadata management , feature stores , model versioning , A/B testing , and monitoring systems Familiarity with LLMOps, DataOps (Airflow, dbt), and streaming architectures Soft Skills Exceptional leadership and mentoring skills Excellent written and verbal communication Ability to work independently and cross-functionally in a fast-paced environment Preferred Qualifications Bachelor’s or Master’s in Computer Science, Statistics, or related field (Tier-I institutions preferred) PhD in Data Science, Machine Learning, or related field (with 8+ years of relevant experience) Publications or conference presentations in ML/AI/DS fields Spanish language proficiency is a plus Nice to Have Experience in fintech, risk, fraud, or payments Exposure to model fairness, explainability, and responsible AI frameworks Familiarity with LLMOps stacks (OpenLLM, LangChain, Guardrails) and prompt engineering for GPT-based models Languages English: Advanced proficiency Spanish: Nice to have Why Join Us Competitive salary and equity Remote-first flexibility + in-person offsites Annual learning budget + global conference participation Ownership-driven culture, fast iteration cycles, low bureaucracy

We're Hiring: Data Scientist Databricks & ML Deployment Expert Location: Mumbai/Pune Experience: 38 Years Apply Now! Are you passionate about deploying real-world machine learning solutions? We're looking for a versatile Data Scientist with deep expertise in Databricks, PySpark , and end-to-end ML deployment to drive impactful projects in the Retail and Automotive domains. What Youll Do Develop scalable ML models (Regression, Classification, Clustering) Deliver advanced use cases like CLV modeling , Predictive Maintenance , and Time Series Forecasting Design and automate ML workflows on Databricks using PySpark Build and deploy APIs to serve ML models (Flask, FastAPI, Django) Own model deployment and monitoring in production environments Work closely with Data Engineering and DevOps teams for CI/CD integration Optimize pipelines and model performance (code & infrastructure level) Must-Have Skills Strong hands-on with Databricks and PySpark Proven track record in ML model development & deployment (min. 2 production deployments) Solid grasp of Regression, Classification, Clustering & Time Series Proficiency in SQL , workflow automation, and ELT/ETL processes API development (Flask, FastAPI, Django) CI/CD, deployment automation, and ML pipeline optimization Familiarity with Medallion Architecture Domain Expertise Retail : CLV, Pricing, Demand Forecasting Automotive : Predictive Maintenance, Time Series Nice to Have MLflow, Docker, Kubernetes Cloud: Azure, AWS, or GCP If you're excited to build production-ready ML systems that create real business impact, we want to hear from you! Apply Now to chaity.mukherjee@celebaltech.com.

Sr MLOps Engineer Experience: 5 - 7 Years Exp Salary : 15 to 20 LPA Preferred Notice Period: Within 30 Days Shift: 10:00AM to 7:00PM IST Opportunity Type: Hybrid (Ahmedabad) Placement Type: Permanent (*Note: This is a requirement for one of Uplers' Clients) Must have skills required : ML model deployment, MLOps, Monitoring Inferenz(One of Uplers' Clients) is Looking for: Sr MLOps Engineer who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you. Role Overview Description About Inferenz At Inferenz, our team of innovative technologists and domain experts help accelerating the business growth through digital enablement and navigating the industries with data, cloud and AI services and solutions. We dedicate our resources to increase efficiency and gain a greater competitive advantage by leveraging various next generation technologies. Our technology expertise has helped us delivering the innovative solutions in key industries such as Healthcare & Life Sciences, Consumer & Retail, Financial Services and Emerging industries. About The Role: Job Overview: Building the machine learning production infrastructure (or MLOps) is the biggest challenge most large companies currently have in making the transition to becoming an AI-driven organization. We are looking for a highly skilled MLOps Engineer to join our team. As an MLOps Engineer, you will be responsible for designing, implementing, and maintaining the infrastructure that supports the deployment, monitoring, and scaling of machine learning models in production. You will work closely with data scientists, software engineers, and DevOps teams to ensure seamless integration of machine learning models into our production systems. The job is NOT for you if: You dont want to build a career in AI/ML. Becoming an expert in this technology and staying current will require significant self-motivation. You like the comfort and predictability of working on the same problem or code base for years. The tools, best practices, architectures, and problems are all going through rapid change — you will be expected to learn new skills quickly and adapt. Key Responsibilities: Model Deployment: Design and implement scalable, reliable, and secure pipelines for deploying machine learning models to production. Infrastructure Management: Develop and maintain infrastructure as code (IaC) for managing cloud resources, compute environments, and data storage. Monitoring and Optimization: Implement monitoring tools to track the performance of models in production, identify issues, and optimize performance. Collaboration: Work closely with data scientists to understand model requirements and ensure models are production ready. Automation: Automate the end-to-end process of training, testing, deploying, and monitoring models. Continuous Integration/Continuous Deployment (CI/CD): Develop and maintain CI/CD pipelines for machine learning projects. Version Control: Implement model versioning to manage different iterations of machine learning models. Security and Governance: Ensure that the deployed models and data pipelines are secure and comply with industry regulations. Documentation: Create and maintain detailed documentation of all processes, tools, and infrastructure. Qualifications: 5+ years of experience in a similar role (DevOps, DataOps, MLOps, etc.) Bachelor’s or master’s degree in computer science, Engineering, or a related field. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) Strong understanding of machine learning lifecycle, data pipelines, and model serving. Proficiency in programming languages such as Python, Shell scripting, and familiarity with ML frameworks (TensorFlow, PyTorch, etc.). Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.) Experience with CI/CD tools like Jenkins, GitLab CI, or similar Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent) Strong software engineering skills in complex, multi-language systems Comfort with Linux administration Experience working with cloud computing and database systems Experience building custom integrations between cloud-based systems using APIs Experience developing and maintaining ML systems built with open-source tools Experience developing with containers and Kubernetes in cloud computing environments Familiarity with one or more data-oriented workflow orchestration frameworks (MLFlow, KubeFlow, Airflow, Argo, etc.) Ability to translate business needs to technical requirements Strong understanding of software testing, benchmarking, and continuous integration Exposure to machine learning methodology and best practices Understanding of regulatory requirements for data privacy and model governance. Preferred Skills: Excellent problem-solving skills and ability to troubleshoot complex production issues. Strong communication skills and ability to collaborate with cross-functional teams. Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack). Knowledge of database systems (SQL, NoSQL). Experience with Generative AI frameworks Preferred cloud-based or MLOps/DevOps certification (AWS, GCP, or Azure) How to apply for this opportunity: Easy 3-Step Process: 1. Click On Apply! And Register or log in on our portal 2. Upload updated Resume & Complete the Screening Form 3. Increase your chances to get shortlisted & meet the client for the Interview! About Our Client: At Inferenz, our team of innovative technologists and domain experts help accelerating the business growth through digital enablement and navigating the industries with data, cloud and AI services and solutions. We dedicate our resources to increase efficiency and gain a greater competitive advantage by leveraging various next generation technologies. Our technology expertise has helped us delivering the innovative solutions in key industries such as Healthcare & Life Sciences, Consumer & Retail, Financial Services and Emerging industries.. About Uplers: Our goal is to make hiring and getting hired reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant product and engineering job opportunities and progress in their career. (Note: There are many more opportunities apart from this on the portal.) So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Key Responsibilities: AI/ML Architecture & Development Architect and implement end-to-end AI/ML solutions using Gen AI and LLMs tailored to business use cases. Design, fine-tune, and deploy large language models such as OpenAI GPT-4o, Gemini, Claude, LLaMA 3.2, and Phi. Build and scale production-ready applications using frameworks like FastAPI, Django, or similar. Develop, maintain, and optimize MLOps pipelines for automated model training, deployment, monitoring, and governance. Generative AI & NLP Expertise Lead the development and integration of generative AI models for applications including summarization, Q&A, sentiment analysis, and translation. Apply NLP and deep learning to enhance performance and reliability of models for complex user interactions. Engage in prompt engineering, vector DB integration, and fine-tuning using Azure OpenAI Service or equivalent platforms on AWS/GCP. System Design & Integration Collaborate closely with data engineering teams to build and manage scalable, cloud-native solutions. Design and deploy event-driven architectures and real-time data processing systems. Work with microservice architectures, containerization tools (Kubernetes, Docker), and cloud platforms (Azure/AWS/GCP). Frameworks & Tooling Use advanced frameworks like LangChain, LlamaIndex, Semantic Kernel, and AutoGen to build scalable LLM applications. Work extensively with data processing tools such as Apache Spark, TensorFlow, PyTorch, Pandas, and Scikit-learn. Technical Leadership Lead cross-functional AI teams and mentor junior engineers and data scientists. Establish and enforce development standards, best practices, and code quality benchmarks. Stay up-to-date with research and contribute to open-source initiatives where applicable. Project & Stakeholder Management Interface with business stakeholders to understand requirements, define AI/ML strategies, and deliver impactful solutions. Handle multiple engagements simultaneously while ensuring timely and high-quality project delivery. Support pre-sales and solutioning efforts including RFPs, RFIs, and client presentations. Required Qualifications: Proven expertise in designing and implementing LLM-based and Gen AI solutions. Hands-on experience with OpenAI, Claude, Gemini, LLaMA 3.2, Phi, and other foundational/open-source models. Strong command over NLP, deep learning, predictive analytics, and data modeling. Proficiency in cloud platforms (Azure preferred; AWS/GCP also acceptable), especially cloud-native and AI tools. Experience with distributed systems, APIs, event-driven architecture, and real-time data streaming. Solid experience with DevOps tools including Azure DevOps, MLflow, or other MLOps platforms. Strong understanding of user interaction patterns with large datasets and search systems. Knowledge of vector databases and semantic search (e.g., Pinecone, FAISS, Weaviate, etc.). Preferred Attributes: Demonstrated success leading AI projects from conception to deployment. Strong business acumen with ability to map AI solutions to business needs. Excellent problem-solving, communication, and collaboration skills. Experience working in Agile environments and managing multi-disciplinary teams.

Hiring API Developer (35 yrs) – Exp in REST/GraphQL APIs, AWS (Lambda, API Gateway, EKS), Databricks, Docker, Kubernetes, ML model deployment. Location: Hyderabad. Full-Time |

We are hiring Senior Machine Learning Engineer for an MNC Job Type : Direct , Fulltime role Location : PAN India (Remote) Senior Machine Learning Engineer Responsibilities Develop, implement, and maintain machine learning models using scikit-learn and SciPy. Build and deploy ML models for production use cases. Work with regression models and optimization techniques. Develop and integrate APIs using the Flask framework. Utilize GCP services (App Engine, Cloud Tasks, Dataflow, BigQuery, Bigtable, Vertex AI). Optimize CI/CD pipelines using Azure DevOps. Collaborate with cross-functional teams to deploy scalable ML solutions. Qualifications Strong proficiency in Python and core ML libraries Scikit-learn and SciPy. Hands-on experience with regression models and optimization techniques. Experience with Flask for API development and deployment. Proficiency in GCP services and ML operations on cloud infrastructure. Experience with CI/CD tools, especially Azure DevOps. Solid understanding of data structures, algorithms, and software engineering practices. Familiarity with Agile methodologies and technical documentation. Strong analytical, communication, and problem-solving skills.

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. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for 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 3. Team Management a. Talent Management i. Support on boarding and training to enhance capability & effectiveness Deliver No. Performance Parameter Measure 1. Demand generation # PoC supported 2. Revenue generation through delivery Timeliness, customer success stories, customer use cases 3. Capability Building & Team Management # Skills acquired Mandatory Skills: Data Analysis.

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. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for 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 3. Team Management a. Talent Management i. Support on boarding and training to enhance capability & effectiveness Deliver No. Performance Parameter Measure 1. Demand generation # PoC supported 2. Revenue generation through delivery Timeliness, customer success stories, customer use cases 3. Capability Building & Team Management # Skills acquired Mandatory Skills: Data Analysis.

Responsibilities: Design and develop AI/ML models Process large dataset Build Python pipeline or React UIs deploy models as APIs or UI features Collaborate with teams, test models, present results Maintain clear documentation of tools and workflows

Wipro Limited (NYSEWIT, BSE507685, NSEWIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com. About The Role 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. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for 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 3. Team Management a. Talent Management i. Support on boarding and training to enhance capability & effectiveness ? Deliver No. Performance Parameter Measure 1. Demand generation # PoC supported 2. Revenue generation through delivery Timeliness, customer success stories, customer use cases 3. Capability Building & Team Management # Skills acquired ? ? Mandatory Skills: Data Analysis. Experience3-5 Years. Reinvent your world. We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention. Come to Wipro. Realize your ambitions. Applications from people with disabilities are explicitly welcome.

About The Role 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 % ? ? Reinvent your world. We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention. Come to Wipro. Realize your ambitions. Applications from people with disabilities are explicitly welcome.

About The Role 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: Python for Data Science. Experience5-8 Years. Reinvent your world. We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention. Come to Wipro. Realize your ambitions. Applications from people with disabilities are explicitly welcome.

Job Descriptio n: Must have experience in AI Enterprises Architecture. Hands on experience in hybrid cloud platforms ( AWS, Azure, GCP). Should have experience in AI Infrastructure Architect, Design, Development, Deployment or Implementation. Expertise in AI and machine learning (ML) technologies with automation tools such as Terraform, Ansible, and Kubernetes for AI environments. Good knowledge of high-performance computing (HPC) for AI workloads, including GPU/TPU architectures. Preferable Candidate Profile: Looking for 7+ years of experience in AI Enterprises Architecture/AI Infrastructure Solution Architect preferable from Service Based Company with exposure of multiple industries projects.

Role: Data Science Leader Experience: 10-15 years of overall experience, with at least 5+ years in Data science roles along with 24 years in a Leadership or Managerial capacity. Technical Skills: Data Science & Machine Learning Deep understanding of statistical modeling, predictive analytics, clustering, NLP, and time series forecasting. Strong grasp of model evaluation, fairness, explainability, and business alignment. Programming Proficient in Python (or R) with experience in data science libraries like pandas, NumPy, scikit-learn, TensorFlow, or PyTorch. Ability to read and review code, debug, and advise on best practices. Cloud Computing Working knowledge of at least one major cloud platform (AWS, GCP, Azure). Experience with cloud-native tools for data storage (S3, BigQuery), compute (EC2, GKE, Lambda), and ML services (SageMaker, Vertex AI, Azure ML). Data Engineering Fundamentals Understanding of data pipelines, ETL/ELT processes. Familiarity with tools like Airflow, dbt, Spark, SQL. Data Visualization Experience with dashboards and reporting tools (Tableau, Power BI, Looker, or custom visualizations using Plotly/Altair). Skilled in transforming complex outputs into clear, compelling narratives for non-technical stakeholders. MLOps / Deployment Familiarity with modern ML development and deployment practices. Basic understanding of deploying models to production, CI/CD pipelines, and monitoring. Generative AI Familiarity with GenAI concepts, including large language models (LLMs), embeddings, prompt engineering, and RAG pipelines. Familiarity with tools and APIs like OpenAI, Hugging Face, LangChain. Leadership & People Management Team Management Experience leading and mentoring teams of 510 individuals across varying levels. Proven track record of building and scaling Data science teams, delivering impactful projects Conduct performance reviews, manage career growth, and foster a healthy team culture. Cross-Functional Collaboration Proven ability to work closely with product, engineering, marketing, and business teams. Hiring & Talent Development Skilled in identifying top talent, conducting interviews, onboarding, and team capability building. Project & Stakeholder Management Project Management Experienced in managing multiple projects simultaneously. Comfortable with Agile methodologies, sprint planning, and delivery tracking. Stakeholder Communication Translating technical insights into business terms. Communicates technical insights clearly to senior executives. Problem Solving & Scope Management Ability to break down ambiguous business problems into solvable components. Define scope and ensure projects align with business impact. Strategic Thinking Aligns team objectives with company vision and business goals. Drives roadmap planning, and long-term capability building. Business Acumen Domain Knowledge Deep understanding of any one business vertical among the following e.g., telecom, BFSI, fintech, e-commerce, healthcare etc. Impact Orientation Focus on delivering measurable business value from data science efforts. Strong grasp of metrics, KPIs, and ROI-driven thinking. Strategic Thinking Ability to align data science efforts with long-term business goals. Soft Skills Exceptional communication, both verbal and written. Decision-Making: Balanced between data, intuition, team input and strategic vision. Empathy & Emotional Intelligence: Especially for managing team dynamics and motivation. Adaptability: In the face of changing priorities or business goals and organizational change.

Gen AI+AWS Skill-Gen AI,AWS,AI Platform,Python,Tensorflow,Langchain,LLM Model,ML Development, AWS Lambda,AWS Bedrock,Data Extraction Exp-3-9YRS In Gen AI AWS PKG Upto-25LPA Loc- Bang, Pune NP-Imm-30Days Ritika-8587970773 ritikab.imaginators@gmail.com Required Candidate profile Gen AI + AWS Mandatory Skill-Gen AI, AWS,AI Platform, Python, Tensor flow, Lang chain, LLM Model, ML Development, AWS Lambda, AWS Bedrock, AWS AI, Data Extraction, GEN AI Solution, RPA Tool

Gen AI+AWS Skill-Gen AI,AWS,AI Platform,Python,Tensorflow,Langchain,LLM Model,ML Development, AWS Lambda,AWS Bedrock,Data Extraction Exp-4-12YRS In Gen AI AWS PKG Upto-25LPA Loc-Bang, Pune NP-Imm-30Days Ritika-8587970773 ritikab.imaginators@gmail.com Required Candidate profile Gen AI + AWS Mandatory Skill-Gen AI, AWS,AI Platform, Python, Tensor flow, Lang chain, LLM Model, ML Development, AWS Lambda, AWS Bedrock, AWS AI, Data Extraction, GEN AI Solution, RPA Tool

Greetings from Peoplefy Infosolutions !!! We are hiring for one of our reputed MNC client based in Pune . We are looking for candidates with 7 + years of experience in below skills - Primary skills : Cloud -google cloud preferred but cloud any will do ML deployment using Jenkins/Harness Python Kubernetes terraform Interested candidates for above position kindly share your CVs on chitralekha.so@peoplefy.com with below details - Experience : CTC : Expected CTC : Notice Period : Location :

We are Hiring Senior Python with Machine Learning Engineer Level 3 for a US based IT Company based in Hyderabad. Candidates with minimum 7 Years of experience in python and machine learning can apply. Job Title : Senior Python with Machine Learning Engineer Level 3 Location : Hyderabad Experience : 7+ Years CTC : 28 LPA - 30 LPA Working shift : Day shift Job Description: We are seeking a highly skilled and experienced Python Developer with a strong background in Machine Learning (ML) to join our advanced analytics team. In this Level 3 role, you will be responsible for designing, building, and deploying robust ML pipelines and solutions across real-time, batch, event-driven, and edge computing environments. The ideal candidate will have extensive hands-on experience in developing and deploying ML workflows using AWS SageMaker , building scalable APIs, and integrating ML models into production systems. This role also requires a strong grasp of the complete ML lifecycle and DevOps practices specific to ML projects. Key Responsibilities: Develop and deploy end-to-end ML pipelines for real-time, batch, event-triggered, and edge environments using Python Utilize AWS SageMaker to build, train, deploy, and monitor ML models using SageMaker Pipelines, MLflow, and Feature Store Build and maintain RESTful APIs for ML model serving using FastAPI , Flask , or Django Work with popular ML frameworks and tools such as scikit-learn , PyTorch , XGBoost , LightGBM , and MLflow Ensure best practices across the ML lifecycle: data preprocessing, model training, validation, deployment, and monitoring Implement CI/CD pipelines tailored for ML workflows using tools like Bitbucket , Jenkins , Nexus , and AUTOSYS Design and maintain ETL workflows for ML pipelines using PySpark , Kafka , AWS EMR , and serverless architectures Collaborate with cross-functional teams to align ML solutions with business objectives and deliver impactful results Required Skills & Experience: 5+ years of hands-on experience with Python for scripting and ML workflow development 4+ years of experience with AWS SageMaker for deploying ML models and pipelines 3+ years of API development experience using FastAPI , Flask , or Django 3+ years of experience with ML tools such as scikit-learn , PyTorch , XGBoost , LightGBM , and MLflow Strong understanding of the complete ML lifecycle: from model development to production monitoring Experience implementing CI/CD for ML using Bitbucket , Jenkins , Nexus , and AUTOSYS Proficient in building ETL processes for ML workflows using PySpark , Kafka , and AWS EMR Nice to Have: Experience with H2O.ai for advanced machine learning capabilities Familiarity with containerization using Docker and orchestration using Kubernetes For further assistance contact/whatsapp : 9354909517 or write to hema@gist.org.in

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. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for 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 3. Team Management a. Talent Management i. Support on boarding and training to enhance capability & effectiveness Deliver No. Performance Parameter Measure 1. Demand generation # PoC supported 2. Revenue generation through delivery Timeliness, customer success stories, customer use cases 3. Capability Building & Team Management # Skills acquired Mandatory Skills: Data Analysis. Experience3-5 Years.

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: Data Science. Experience8-10 Years.