98 Ml Pipelines Jobs

5 years of experience inMLOpsand building ML pipelines Deep understanding of the MLOps lifecycle and automation of ML workflows Proficient in Python 310 and related libraries such as pandas NumPy and TensorFlow Strong experience in GPU accelerators and CUDA for model training and optimization Proven experience in model monitoring drift detection and maintaining model accuracy over time Familiarity with CICD pipelines Docker Kubernetes and cloud infrastructure Strong problem solving skills with the ability to work in a fastpaced environment Preferred Qualifications Experience with tools like Evidently AI for model monitoring and drift detection Knowledge of data versioning and model version control techniques Familiarity with TensorFlow Extended TFX or other ML workflow orchestration frameworks Excellent communication and collaboration skills with the ability to work crossfunctionally across teams

Role & responsibilities Experience working on AWS Cloud is a must, Data Science, Machine Learning , LLP, Deployment Experience. Preferred candidate profile Machine learning engineer having minimum 7 years of relevant experience & Aws minimum 3 Years.

Skills Required: ML Engineer Strong Python programming skills Hands-on experience with TensorFlow, especially in training custom models/modules Experience working with OpenAI's Whisper ASR (Automatic Speech Recognition) model Following is the skillset: Primary Skills - Llama, Whisper, DistilBert, Spacy, any document database, any vector database, model training and finetuning Secondary Skills TensorFlow, any agentic framework

Job Role: ML Engineer Skills Required: ML Engineer Strong Python programming skills Hands-on experience with TensorFlow, especially in training custom models/modules Experience working with OpenAI's Whisper ASR (Automatic Speech Recognition) model

Responsibilities: * Develop immunotherapy strategies using computational methods. * Collaborate with cross-functional teams on research. * *Education* PhD/MSc in Immunology, Cancer Biology, Computational Biology, Bioinformatics, or related field.

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Operations Good to have skills : NAMinimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Machine Learning Engineer/MLOps Expert, you will engage in the operationalization of Machine Learning Models that leverage artificial intelligence tools and cloud AI services. Your typical day will involve designing and implementing production-ready ML system, ensuring high-quality standards are met. Roles & Responsibilities:- Continuously evaluate and improve existing processes to enhance efficiency.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Facilitate knowledge sharing sessions to enhance team skills and capabilities.- Monitor project progress and ensure alignment with strategic goals. Professional & Technical Skills: - ML Pipeline Development:Design, build, and maintain scalable pipelines for model training to support our AI initiatives.- Model Deployment & Serving:Deploy machine learning models as robust, secure services containerize models with Docker and serve them via FastAPI on AWS ensuring low-latency predictions for marketing applications. Manage Batch inference and Realtime inference.- CI/CD Automation:Implement continuous integration and delivery (CI/CD) pipelines for ML projects. Automate testing, model validation, and deployment workflows using tools like GitHub Actions to accelerate delivery.- Model Lifecycle Management:Orchestrate the end-to-end ML lifecycle, including versioning, packaging, and registering models. Maintain a model repository/registry (MLflow or similar) for reproducibility and governance from experimentation through production. Experience on MLFlow and Airflow is mandatory- Monitoring & Optimization:Monitor model performance, data drift, and system health in production. Set up alerts and dashboards and proactively initiate model retraining or tuning to sustain accuracy and efficiency over time.- Must To Have Skills: Proficiency in Machine Learning Operations.- Strong understanding of cloud-based AI services and deployment strategies.- Should have Multi Cloud skills- Experience with Machine learning frameworks- Ability to implement and optimize machine learning models for production environments. Additional Information:- The candidate should have minimum 7.5 years of experience in Machine Learning Operations.- This position is based at our Bengaluru office.- A 15 years full time education is required. Qualification 15 years full time education

Role Description As a Senior ML Engineer / ML Ops - GCP Specialist at Incedo, you will be responsible for building and deploying machine learning models in production environments. You will work with data scientists, data engineers, and software developers to design and implement machine learning pipelines. You will be skilled in programming languages such as Python or Java and have experience in ML tools such as TensorFlow or PyTorch. You will be responsible for ensuring that models are scalable, efficient, and can be deployed in production environments. Roles & Responsibilities: Designing and developing machine learning (ML) models and algorithms Implementing and maintaining ML pipelines and workflows Collaborating with data scientists and analysts to deploy and monitor ML models Developing and implementing ML deployment and monitoring strategies Providing guidance and mentorship to junior ML engineers Troubleshooting and resolving ML platform issues Technical Skills Skills Requirements: Proficiency in programming languages such as Python, Java, or Scala. Understanding of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras. Knowledge of cloud computing and containerization technologies such as Docker, Kubernetes, or AWS. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Nice-to-have skills Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

As a Senior ML Engineer / ML Ops - GCP Specialist at Incedo, you will be responsible for building and deploying machine learning models in production environments. You will work with data scientists, data engineers, and software developers to design and implement machine learning pipelines. You will be skilled in programming languages such as Python or Java and have experience in ML tools such as TensorFlow or PyTorch. You will be responsible for ensuring that models are scalable, efficient, and can be deployed in production environments. Roles & Responsibilities: Designing and developing machine learning (ML) models and algorithms Implementing and maintaining ML pipelines and workflows Collaborating with data scientists and analysts to deploy and monitor ML models Developing and implementing ML deployment and monitoring strategies Providing guidance and mentorship to junior ML engineers Troubleshooting and resolving ML platform issues Technical Skills Skills Requirements: Proficiency in programming languages such as Python, Java, or Scala. Understanding of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras. Knowledge of cloud computing and containerization technologies such as Docker, Kubernetes, or AWS. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Nice-to-have skills Qualifications Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

We are looking for a highly skilled and motivated Lead Data Scientist to join our team. In this role, you will leverage cutting-edge AI and machine learning technologies to address new and unique challenges, design innovative data science solutions, and deliver projects that exceed client expectations. As a leader, you will manage a team of data scientists, collaborate with cross-functional data teams, and provide strategic and technical direction in data science while driving innovation in our product and solution offerings. You should have strong statistical and machine learning intuition along with the ability to design, develop, and deploy end-to-end data science solutions, POCs, and production-grade applications. Proficiency in Python with OOP principles, experience in developing APIs using Flask or Fast API frameworks, integration knowledge with front-end applications, expertise in version control systems, familiarity with task management tools, and proficiency in databases including SQL, NoSQL, and vector databases are essential. Working knowledge of ML pipelines, CI/CD, and experience with at least one of the cloud platforms (Azure, AWS, GCP) is required. Candidates must have a strong understanding of fundamentals and hands-on expertise in at least THREE of the following areas: NLP, Generative AI (NLP), Computer Vision, Time Series Forecasting, or Recommendation Systems and Optimization. Your responsibilities will include leveraging advanced AI and machine learning techniques to address complex business challenges, developing innovative data science solutions, architecting end-to-end generative AI solutions, leading and mentoring a team of data scientists, collaborating with cross-functional teams, ensuring high client satisfaction, promoting innovation, and ideating new approaches for products and solutions. Nice to have skills include hands-on experience with PySpark, Azure AI stack, ETL processes, integration with analytics tools, knowledge of deep learning frameworks, experience with cloud platforms, MLOps practices, project management skills, and proficiency in graph databases. Ideal candidates will have a minimum of 5+ years of experience solving complex machine learning problems, at least 2+ years of hands-on experience in each chosen Core Excellence Area, minimum of 1 year leading and managing ML projects end-to-end, and a Bachelor's degree in computer science, Data Science, or related field (Masters/PG in AI/ML/DS preferred).,

You will be part of the AI squad within the CDO office of the bank, playing a critical role in driving AI adoption and enablement across the bank's functions. Your main responsibility will be to deploy as a member of the functional AI Squads. Your key responsibilities include: Strategy: - Delivering, building, and maintaining solutions for AI use cases and enhancing functionalities of AI tools within the bank. Business: - Accelerate the delivery of AI use cases for various Business & Functions of the bank. - Responsible for implementing product roadmaps, product improvement, building applications with modern architecture design, RESTful web services / APIs, web-based application enhancements for processing large data volumes and real-time streaming, and product deployment with appropriate SDF controls. - Supporting applications in production, analyzing and resolving issues, performing RCA analysis, and implementing solutions. - Acting as a technical subject matter expert and go-to person for all technical requirements within your team. Risk Management: - Adhering to all SDF controls and Data Governance Standards of the bank. Governance: - Developing and implementing change management plans for successful adoption of AI solutions across the organization. - Providing training and support to business users to help them understand and leverage AI tools and technologies. - Fostering a culture of innovation and continuous improvement by promoting the benefits of AI and encouraging experimentation. Regulatory & Business Conduct: - Displaying exemplary conduct and living by the Groups Values and Code of Conduct. - Taking personal responsibility for embedding the highest standards of ethics, regulatory and business conduct across Standard Chartered Bank. - Collaboratively identifying, escalating, mitigating, and resolving risk, conduct, and compliance matters. Key stakeholders include CDO Squads, Business Partners, ITO, internal staff, clients, and 3rd parties. Other responsibilities include embedding Here for good and Groups brand and values, performing other assigned responsibilities under Group, Country, Business, or Functional policies and procedures, identifying and prioritizing AI use cases with significant business value, and developing business cases for AI projects. You are expected to have skills and experience in building and deploying machine learning models, implementing Generative AI solutions, mentoring and guiding a team of machine learning engineers and data scientists, optimizing feature engineering and model tuning, and driving the adoption of advanced ML algorithms. Qualifications: - Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) for building and deploying production-grade machine learning models. - Training in usage and development of LLMs and proficiency in Prompt Engineering. - Language proficiency in English. Standard Chartered is an international bank that values difference, advocates inclusion, and aims to drive commerce and prosperity through unique diversity. They offer core bank funding for retirement savings, medical and life insurance, time-off benefits, flexible working options, proactive wellbeing support, a continuous learning culture, and the opportunity to be part of an inclusive and values-driven organization. If you are looking for a purpose-driven career and want to work for a bank that makes a difference, Standard Chartered welcomes your unique talents and is excited to see what you can bring to the team.,

Key Skills: Technical Skills: Proficiency with Data bricks Lakehouse platform, Delta Lake, Genie, ML Flow (e.g., Data bricks Certified Data Engineer Associate) is a plus. SQL and NoSQL: Experienced working with both SQL and NoSQL data sources (e.g., MySQL, PostgreSQL, MongoDB etc.) Strong knowledge of Spark, especially in PySpark or Scala, for data transformation. Proficiency in Python, R and other programming languages used in data processing. Experience with cloud platforms like Azure, AWS, particularly Azure storage & services Knowledge of ML Pipelines, data streaming platforms (e.g., Apache Kafka, AWS Kinesis). Familiarity with data visualization tools (e.g., Tableau, Power BI, Looker) Educational Qualification: Education: Bachelors degree in Computer Science, Engineering/MCA, or a related field (Masters preferred) 3+ years of experience as a Data Engineer, with hands-on experience in Databricks

As a skilled and passionate Platform Architect specializing in GenAI/LLM Systems, you will be responsible for architecting scalable, cloud-native infrastructure to support enterprise-grade GenAI and LLM-powered applications. Your role will involve designing and deploying secure, reliable API gateways, orchestration layers (such as Airflow, Kubeflow), and CI/CD workflows for ML and LLM pipelines. Collaboration with data and ML engineering teams will be essential to enable low-latency LLM inference and vector-based search platforms across GCP (or multi-cloud). You will define and implement a semantic layer and data abstraction strategy to facilitate consistent and governed consumption of data across LLM and analytics use cases. Additionally, implementing robust data governance frameworks including role-based access control (RBAC), data lineage, cataloging, observability, and metadata management will be part of your responsibilities. Your role will involve guiding architectural decisions around embedding stores, vector databases, LLM tooling, and prompt orchestration (e.g., LangChain, LlamaIndex), as well as establishing compliance and security standards to meet enterprise SLA, privacy, and auditability requirements. To excel in this role, you should have at least 7 years of experience as a Platform/Cloud/Data Architect, ideally within GenAI, Data Platforms, or LLM systems. Strong cloud infrastructure experience on GCP (preferred), AWS, or Azure, including Kubernetes, Docker, Terraform/IaC is required. Demonstrated experience in building and scaling LLM-powered architectures using OpenAI, Vertex AI, LangChain, LlamaIndex, etc. will be a significant advantage. You should also have familiarity with semantic layers, data catalogs, lineage tracking, and governed data delivery across APIs and ML pipelines. A track record of deploying production-grade GenAI/LLM services that meet performance, compliance, and enterprise integration requirements is essential. Strong communication and cross-functional leadership skills are also desired, as you will be required to translate business needs into scalable architecture.,

We are seeking individuals who are smart, self-driven, high-energy, and possess exceptional communication skills along with intellectual curiosity and a strong passion for technology within the Machine Learning space. Our analysts exhibit a deep understanding of one or more areas in the Retail and CPG domain, coupled with robust business acumen and excellent soft skills. Proficiency in technology is also a key requirement. The ideal candidate must possess the following technical skills: - MLOps Implementation and Support Experience - Expertise in Python Programming with a minimum of 4-5 years of experience - Working knowledge of DevOps with implementation experience in at least 1 or 2 projects - Proficiency in Microsoft Azure Cloud - Familiarity with operational experience - Knowledge of Azure services required for deployment such as Azure Databricks and Azure DevOps Setup - Adherence to coding standards like flake8 - Automation technology and process improvement for deployed projects - Agile trained to manage team efforts and track progress through JIRA Desirable skills include understanding of domains such as Retail, Supply Chain, Logistics, or Manufacturing. In terms of soft skills, strong verbal and written communication skills, the ability to work effectively in a team, customer focus, ownership, urgency, and the capability to manage multiple priorities in a fast-paced environment are essential. Collaborating effectively with team members to uphold high credibility is also crucial. Candidates should have 3-5 years of experience in Machine Learning, Azure, and MLOps. Key responsibilities include translating business requirements into technical specifications, delivering MLOps solutions successfully in client consulting environments, identifying and solving key business problems, developing solutions, analyzing data, presenting conclusions to clients, assisting in operationalization metrics for ML models, managing ML pipelines, debugging pipeline issues, and engaging with business stakeholders to provide progress updates and issue fixes. Educational requirements may include a Bachelor of Engineering or Bachelor of Technology in any stream with a consistent academic track record, or a Bachelor's degree in a quantitative discipline such as Operations Research, Statistics, Mathematics, or relevant coursework with consistent academic performance. Additional academic qualifications such as a Master's degree in Science, Operation Research, Mathematics, Statistics, or a PhD in any related field are advantageous. Preferred skills include familiarity with Analytics Functional Business Analyst technology.,

You are an experienced professional with over 13 years of total experience, specializing in machine learning. You have a proven track record of delivering impactful solutions in Natural Language Processing (NLP), machine vision, and Artificial Intelligence (AI). Your proficiency includes programming languages like Python or R, as well as experience with data manipulation libraries such as Pandas and NumPy. You possess a strong understanding of statistical concepts and techniques, applying them effectively to real-world problems. Your expertise extends to deep learning frameworks like TensorFlow, PyTorch, or JAX, along with machine learning libraries like scikit-learn. You have proficient experience with Generative AI frameworks such as GANs, VAEs, prompt engineering, and retrieval-augmented generation (RAG), applying them to real-world scenarios. Additionally, you have exposure to graph-based models, knowledge graphs, and related query languages. In your role, you demonstrate hands-on skills in data engineering and building robust ML pipelines. You are experienced in working with personalization engines and integrating digital marketing platforms. Your responsibilities include architecting scalable, cloud-based AI/ML solutions on platforms like AWS, Azure, or GCP, integrating data pipelines and AI services. You possess excellent communication skills and collaborate effectively with cross-functional teams. Your daily tasks involve writing and reviewing high-quality code, understanding clients" business use cases and technical requirements, and translating them into elegant technical designs. You are adept at identifying different solutions and selecting the best option that aligns with clients" needs. Defining guidelines and benchmarks for non-functional requirements (NFRs) during project implementation is also part of your responsibilities. Moreover, you write and review design documents, explaining the overall architecture, framework, and high-level design of applications for developers. You review architecture and design aspects like extensibility, scalability, security, design patterns, user experience, and NFRs, ensuring adherence to best practices. You develop the overall solution for defined functional and non-functional requirements, defining technologies, patterns, and frameworks to bring it to fruition. Your qualifications include a Bachelor's or Master's degree in computer science, Information Technology, or a related field.,

As a Lead Machine Learning Data Engineer with 10-15 years of experience, you will be responsible for designing, developing, and optimizing ML models for NLP, CV, and data-driven applications. You will work with transformer architectures, multimodal AI models, and generative AI techniques to implement ML pipelines, including data preprocessing, feature engineering, training, evaluation, and deployment. Your role will involve designing and implementing a Speech LLM-based virtual assistant, along with developing and maintaining Python code for audio capture, encoding, modality fusion, LLM interaction, and text output. Additionally, you will integrate and configure pre-trained models for audio encoding, LLM, and audio decoding, while staying up-to-date with the latest research and advancements in Speech LLMs, audio processing, and related fields. It will be your responsibility to document the system design, code, and experimental results, as well as architect scalable, production-ready ML systems integrating MLOps best practices. You will also set the technical direction, ensuring best practices in AI research, model deployment, and system scalability. This role will require you to work 5 days a week in a hybrid mode, with one week working from the office in a month, in either Bangalore or Chennai. The ideal candidate should be able to join immediately or with a notice period of a maximum of 15 days.,

You are seeking a Lead - Python Developer / Tech Lead to take charge of backend development and oversee a team handling enterprise-grade, data-driven applications. In this role, you will have the opportunity to work with cutting-edge technologies such as FastAPI, Apache Spark, and Lakehouse architectures. Your responsibilities will include leading the team, making technical decisions, and ensuring timely project delivery in a dynamic work environment. Your primary duties will involve mentoring and guiding a group of Python developers, managing task assignments, maintaining code quality, and overseeing technical delivery. You will be responsible for designing and implementing scalable RESTful APIs using Python and FastAPI, as well as managing extensive data processing tasks using Pandas, NumPy, and Apache Spark. Additionally, you will drive the implementation of Lakehouse architectures and data pipelines, conduct code reviews, enforce coding best practices, and promote clean, testable code. Collaboration with cross-functional teams, including DevOps and Data Engineering, will be essential. Furthermore, you will be expected to contribute to CI/CD processes, operate in Linux-based environments, and potentially work with Kubernetes or MLOps tools. To excel in this role, you should possess 9-12 years of total experience in software development, with a strong command of Python, FastAPI, and contemporary backend frameworks. A profound understanding of data engineering workflows, Spark, and distributed systems is crucial. Experience in leading agile teams or fulfilling a tech lead position is beneficial. Proficiency in unit testing, Linux, and working in cloud/data environments is required, while exposure to Kubernetes, ML Pipelines, or MLOps would be advantageous.,

Join as Principal AI, Blockchain & Payments Architect (Remote). Lead AI/ML & Blockchain integration in a cutting-edge payments platform. FinTech, Java, Python, AI, DLT, global rails. DM or send resume to suresh@goldenpicktech.com. Flexi working Work from home Performance bonus

The Product Engineer AI-Powered Developer Tools (On-Prem) position based in Tower 1, World Trade Center, Kharadi, Pune offers a full-time, in-office work arrangement. As a part of the core engineering squad, you will be involved in building air-gapped, AI-powered developer tooling designed to operate completely behind customer firewalls. Your role will entail transforming ideas and prototypes into refined features, collaborating closely with architects, and delivering code that enhances the experience of developers. The product is specifically tailored to function within customer firewalls, incorporating customized LLM models and on-prem systems. Your key responsibilities will include owning features from end to end, encompassing the design, coding, testing, and integration of user-facing features in AI-driven IDE extensions and backend services. You will also be responsible for self-hosted AI wiring by integrating local LLMs, embeddings, and static-analysis models for various functionalities without relying on external endpoints. Additionally, you will contribute to CI/CD & DevOps activities to maintain efficient pipelines, dockerize new services, update Helm/Ansible scripts, and ensure seamless on-prem deployments. Emphasis will also be placed on prioritizing quality by writing various types of tests, monitoring performance metrics, and optimizing latency for a seamless user experience. To excel in this role, you should have a minimum of 5 years of experience in building production-grade software, with expertise in Java, API, microservices, TypeScript/JavaScript, and proficiency in Python or Go (knowledge of Rust/C++ is a plus). Familiarity with Git workflows, Docker, and at least one on-prem K8s/OpenShift environment is essential. Exposure to LLM frameworks or traditional ML pipelines, as well as experience with IaC tools and basic Linux operations, will also be beneficial. If you were a proficient builder before the AI wave, can effectively incorporate AI into your workflow, and are adept at utilizing various tools like Cursor, Claude Code, Google CLI, Windsurf, Replit, and Lovable, you are likely to be a good fit for this role. You should be capable of rapidly developing functional prototypes using AI tools, have a track record of creating products that users love, and prioritize collaboration and momentum over perfection. Smart Analytica offers a stimulating work environment where you can contribute to building the next-generation on-prem AI coding platform. You will have the opportunity for hands-on mentorship from seasoned architects and AI experts in a close-knit team that values craftsmanship, efficiency, and mutual support. If you are ready to play a pivotal role in shaping the future of AI development behind the firewall, please email your resume to hiring@smart-analytica.com with the subject "Product Engineer.",

Educational Requirements MCA,MSc,Bachelor of Engineering,BBA,BCom Service Line Data & Analytics Unit Responsibilities Roles & Responsibilities: Understand the requirements from the business and translate it into an appropriate technical requirement. Responsible for successful delivery of MLOps solutions and services in client consulting environments; Define key business problems to be solved; formulate high level solution approaches and identify data to solve those problems, develop, analyze/draw conclusions and present to client. Assist clients with operationalization metrics to track performance of ML Models Help team with ML Pipelines from creation to execution Guide team to debug on issues with pipeline failures Understand and take requirements on Operationalization of ML Models from Data Scientist Engage with Business / Stakeholders with status update on progress of development and issue fix Setup Standards related to Coding, Pipelines and Documentation Research on new topics, services and enhancements in Cloud Technologies Additional Responsibilities: EEO/ :Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.Infosys provides equal employment opportunities to applicants and employees without regard to race; color; sex; gender identity; sexual orientation; religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability. Technical and Professional Requirements: Preferred Qualifications: Experienced in Agile way of working, manage team effort and track through JIRA High Impact client communication Domain experience in Retail, CPG and Logistics Experience in Test Driven Development and experience in using Pytest frameworks, git version control, Rest APIsThe job may entail extensive travel. The job may also entail sitting as well as working at a computer for extended periods of time. Candidates should be able to effectively communicate by telephone, email, and face to face. Preferred Skills: Technology-Machine learning-data science

The role will oversee the strategic direction and execution of machine learning projects, working closely with data scientists, software engineers, and product teams. The aim is to enhance services through innovative AI/ML solutions, including building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and enhance customer experiences. Key Responsibilities: - Define and drive the strategic vision for machine learning initiatives. - Lead the development and optimization of machine learning models. - Supervise the preprocessing and analysis of large datasets. - Deploy and maintain ML solutions in production environments. - Collaborate with cross-functional teams to integrate ML models into products and services. - Monitor and evaluate the performance of deployed models and make necessary adjustments. - Mentor and guide junior engineers and data scientists. - Ensure adherence to best practices and industry standards in ML development. Minimum Qualifications: - Minimum of 12 years of relevant work experience and a Bachelor's degree or equivalent. - Previous management experience. The company values Inclusion, Innovation, Collaboration, and Wellness, guiding the global team to prioritize customers while taking care of themselves, each other, and communities. Those interested in joining the team can visit https://about.pypl.com/who-we-are/default.aspx. Applicants are encouraged to apply regardless of any confidence gap or imposter syndrome.,

Role & responsibilities Build and deploy production-grade ML pipelines for varied use cases across operations, manufacturing, supply chain, and more Work hands-on in designing, training, and fine-tuning models across traditional ML, deep learning, and GenAI (LLMs, diffusion models, etc.) Collaborate with data scientists to transform exploratory notebooks into scalable, maintainable, and monitored deployments Implement CI/CD pipelines, version control, and experiment tracking using tools like MLflow, DVC, or similar Do shadow deployment and A/B testing of production models Partner with data engineers to build data pipelines that support real-time or batch model inference Ensure high availability, performance, and observability of deployed ML solutions using MLOps best practices Conduct code reviews, performance tuning, and contribute to ML infrastructure improvements Support the end-to-end lifecycle of ML products Contribute to knowledge sharing, reusable component development, and internal upskilling initiatives Preferred candidate profile Bachelor's in Computer Science, Engineering, Data Science, or related field. Masters degree preferred 4–6 years of experience in developing and deploying machine learning models, with significant exposure to MLOps practices Experience in implementing and productionizing Generative AI applications using LLMs (e.g., OpenAI, HuggingFace, LangChain, RAG architectures) Strong programming skills in Python; familiarity with ML libraries such as scikit-learn, TensorFlow, PyTorch Hands-on experience with tools like MLflow, Docker, Kubernetes, FastAPI/Flask, Airflow, Git, and cloud platforms (Azure/AWS) Solid understanding of software engineering fundamentals and DevOps/MLOps workflows Exposure to at least 2-3 industry domains (energy, manufacturing, finance, etc.) preferred Excellent problem-solving skills, ownership mindset, and ability to work in agile cross-functional teams

Hands-on experience of deployment of models on Snowflake, and writing stored procedures for the same, OR Hands-on experience with Cortex AI and its frameworks. Experience in doing indexing, parsing, & Document AI within Cortex. Required Candidate profile Experience in Snowflake data platform and infrastructure Snow-park should be known, Data Science theoretical or DS Candidates should be only from Tamil Nadu

As a Senior ML Engineer / ML Ops - GCP Specialist at Incedo, you will be responsible for building and deploying machine learning models in production environments. You will work with data scientists, data engineers, and software developers to design and implement machine learning pipelines. You will be skilled in programming languages such as Python or Java and have experience in ML tools such as TensorFlow or PyTorch. You will be responsible for ensuring that models are scalable, efficient, and can be deployed in production environments. Roles & Responsibilities: Designing and developing machine learning (ML) models and algorithms Implementing and maintaining ML pipelines and workflows Collaborating with data scientists and analysts to deploy and monitor ML models Developing and implementing ML deployment and monitoring strategies Providing guidance and mentorship to junior ML engineers Troubleshooting and resolving ML platform issues Technical Skills Skills Requirements: Proficiency in programming languages such as Python, Java, or Scala. Understanding of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras. Knowledge of cloud computing and containerization technologies such as Docker, Kubernetes, or AWS. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Nice-to-have skills Qualifications Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

GCP Cloud Architecture. Model Deployment Lifecycle Knowledge of creating Training & Serving Pipeline Familiar with any one of workflow: Kubeflow, Airflow, ML Flow, Argo etc" Strong in Python Adequate SQL skill Must have skill : Python, SQL, ML Engineer (Model Deployment/MLOPS), ML Pipeline-(Kubeflow, Airflow Flow, Argo etc,) Preferred Skill: Pytorch, TensorFlow, Exp in hiper scaler/Cloud Service, Deep learning framework,

The company's beliefs serve as the guiding principles driving the daily operations, centered around core values of Inclusion, Innovation, Collaboration, and Wellness. These values underscore the importance of working collaboratively as a global team, prioritizing customers, self-care, interpersonal relationships, and community involvement. As a key member of the team, your role will focus on spearheading the strategic vision and advancement of cutting-edge machine learning models and algorithms to address intricate challenges. Working closely with data scientists, software engineers, and product teams, you will leverage innovative AI/ML solutions to enhance services. Your responsibilities will include constructing scalable ML pipelines, ensuring data accuracy, and deploying models in production environments to generate valuable business insights and enhance customer experiences. Key Responsibilities: - Define and execute the strategic vision for machine learning initiatives at the organizational level. - Lead the development and optimization of advanced machine learning models. - Supervise the preprocessing and analysis of extensive datasets. - Implement and uphold ML solutions in live production environments. - Collaborate with cross-functional teams to integrate ML models into products and services. - Monitor and assess the performance of deployed models, making necessary refinements. - Provide mentorship and guidance to junior engineers and data scientists. - Publish research outcomes and contribute to industry conversations. - Represent the company at conferences and external events. - Influence the company's AI/ML strategy and contribute to long-term planning. Minimum Qualifications: - A minimum of 18 years of relevant work experience along with a Bachelor's degree or equivalent. - Profound expertise in ML frameworks such as TensorFlow, PyTorch, or scikit-learn. - Extensive hands-on experience with cloud platforms like AWS, Azure, GCP, and tools for data processing and model deployment. - Recognized as an industry authority with a robust publication history. The company offers a range of benefits that support employee well-being and professional growth. To gain insight into our culture and community, visit https://about.pypl.com/who-we-are/default.aspx If you are interested in joining our Talent Community or have any queries regarding your application, please feel free to reach out. We acknowledge the challenges posed by the confidence gap and imposter syndrome, and we encourage all candidates to apply without hesitation.,