515 Mlops Jobs - Page 7

We are seeking a highly skilled AI/ML Engineer to join our team. As an AI/ML Engineer, you will be responsible for designing, implementing, and optimizing machine learning solutions, encompassing traditional models, deep learning architectures, and generative AI systems. Your role will involve collaborating with data engineers and cross-functional teams to create scalable, ethical, and high-performance AI/ML solutions that contribute to business growth. Your key responsibilities will include developing, implementing, and optimizing AI/ML models using both traditional machine learning and deep learning techniques. You will also design and deploy generative AI models for innovative business applications, in addition to working closely with data engineers to establish and maintain high-quality data pipelines and preprocessing workflows. Integrating responsible AI practices to ensure ethical, explainable, and unbiased model behavior will be a crucial aspect of your role. Furthermore, you will be expected to develop and maintain MLOps workflows to streamline training, deployment, monitoring, and continuous integration of ML models. Your expertise will be essential in optimizing large language models (LLMs) for efficient inference, memory usage, and performance. Collaboration with product managers, data scientists, and engineering teams to seamlessly integrate AI/ML into core business processes will also be part of your responsibilities. Rigorous testing, validation, and benchmarking of models to ensure accuracy, reliability, and robustness are essential aspects of this role. To be successful in this position, you must possess a strong foundation in machine learning, deep learning, and statistical modeling techniques. Hands-on experience with TensorFlow, PyTorch, scikit-learn, or similar ML frameworks is required. Proficiency in Python and ML engineering tools such as MLflow, Kubeflow, or SageMaker is also necessary. Experience in deploying generative AI solutions, understanding responsible AI concepts, solid experience with MLOps pipelines, and proficiency in optimizing transformer models or LLMs for production workloads are key qualifications for this role. Additionally, familiarity with cloud services (AWS, GCP, Azure), containerized deployments (Docker, Kubernetes), as well as excellent problem-solving and communication skills are essential. Ability to work collaboratively with cross-functional teams is also a crucial requirement. Preferred qualifications include experience with data versioning tools like DVC or LakeFS, exposure to vector databases and retrieval-augmented generation (RAG) pipelines, knowledge of prompt engineering, fine-tuning, and quantization techniques for LLMs, familiarity with Agile workflows and sprint-based delivery, and contributions to open-source AI/ML projects or published papers in conferences/journals. Join our team at Lucent Innovation, an India-based IT solutions provider, and enjoy a work environment that promotes work-life balance. With a focus on employee well-being, we offer 5-day workweeks, flexible working hours, and a range of indoor/outdoor activities, employee trips, and celebratory events throughout the year. At Lucent Innovation, we value our employees" growth and success, providing in-house training, as well as quarterly and yearly rewards and appreciation. Perks: - 5-day workweeks - Flexible working hours - No hidden policies - Friendly working environment - In-house training - Quarterly and yearly rewards & appreciation,

Role & responsibilities About the Role: Our team is responsible for building the backend components of the GenAI Platform. The Platform offers: Safe, compliant and cost-efficient access to LLMs, including Opensource & Commercial ones, adhering to Experian standards and policies Reusable tools, frameworks and coding patterns to perform various functions involved in either fine-tuning a LLM or developing a RAG-based application What youll do here Design & build backend components of our GenAI platform on AWS. Collaborate with geographically distributed cross-functional teams. Participate in on-call rotation with the rest of the team to handle production incidents. What youll need to succeed Must have skills: At least 7+ years of professional backend web development experience with Python. Experience of AI and RAG Experience with DevOps & IaC tools such as Terraform, Jenkins etc. Experience with MLOps platorms such as AWS Sagemaker, Kubeflow or MLflow. Experience with web development frameworks such as Flask, Django or FastAPI. Experience with concurrent programming designs such as AsyncIO. Experience with any of the public cloud platforms like AWS, Azure, GCP, preferably AWS. Experience with CI/CD practices, tools, and frameworks. Nice to have skills: Experience with Apache Kafka and developing Kafka client applications in Python. Experience with big data processing frameworks, preferably Apache Spark. Experience with containers (Docker) and container platorms like AWS ECS or AWS EKS. Experience with unit and functional testing frameworks. Experience with various Python packaging options such as Wheel, PEX or Conda. Experience with metaprogramming techniques in Python Preferred candidate profile 7 YEARS TO 18 YEARS Permanent, "Python Terraforms AI & RAG MLOps Any cloud (Preferred AWS)"

Job Description : Key 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. Requirements : - 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 Qualifications : - 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.

Job Description : Key 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. Requirements : - 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 Qualifications : - 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.

Job Description : Key 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. Requirements : - 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 Qualifications : - 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.

One of our prestigious client is looking for to hire candidates for the below position Position Type : Sr. Data Scientist Years of Experience: 5 - 7 Years Number of positions: 2 nos Salary / CTC : upto 38 LPA (based on your current salary and on the interview evaluation) Job Summary Responsibilities: Help design and build the next iteration of process automation in Core Map processes employing a highly scalable Big Data infrastructure and machine learning as applied to global-scale digital map-making. Build and test analytic and statistical models to improve a wide variety of both internal data-driven processes for map-making data decisions and system control needs. Act as an expert and evangelist in the areas of data mining, machine learning, statistics, and predictive analysis and modeling. Requirements: MS or PhD in a discipline such as Statistics, Applied Mathematics, Computer Science, or Econometrics with an emphasis or thesis work on one or more of the following: computational statistics/science/engineering, data mining, machine learning, and optimization. Minimum of 5 years related, professional experience. Knowledge of data mining and analytic methods such as regression, classifiers, clustering, association rules, decision trees, Bayesian network analysis, etc. We should have expert-level knowledge in one or more of these areas. Knowledge of Computer Vision, Deep Learning and Point Cloud Processing algorithms. Proficiency with a statistical analysis package and associated scripting language such as Python, R, Matlab, SAS, etc. Programming experience with SQL, shell script, Python, etc. Knowledge of and ideally some experience with MLOps will be preferred. Knowledge of and ideally some experience with tools such as Pig, Hive, etc., for working with big data in Hadoop and/or Spark for data extraction and data prep for analysis. Experience with and demonstrated capability to effectively interact with both internal and external customer executives, technical and non-technical to explain uses and value of predictive systems and techniques. Demonstrated proficiency with understanding, specifying and explaining predictive modeling solutions and organizing teams of other data scientists and engineers to execute projects delivering those solutions. Preferred Qualifications: Development experience with Java and Scala Development experience with Docker Development experience with GIS data Development experience with NoSQL (i.e. DynamoDB) Knowledge of GPU programming (CUDA or OpenCL) on GPU accelerator architecture ================================================================= Please provide us the following information. along with your updated resume: Your Total Experience: Your Relevant Development Experience in Java: Your Relevant Development Experience in Scala programming: Your Relevant Development Experience with Docker: Your Relevant Development Experience with GIS data: Your Relevant Development Experience with NoSQL (i.e. DynamoDB): Your Relevant Experience with GPU programming (CUDA or OpenCL) on GPU accelerator architecture: Your latest Education with year of passing/percentage: Your Certification (any): If yes, Provide the your code or share the Certication copy: Your Notice Period: Is Buyout option available (yes/no): if yes, Do mention the Buyout notice period amount: Your Current Location: Your Preferred Location: Work from Office / Hybrid: Your Current Salary : Your Expected Salary : Any active offer (yes/no) : If yes, do mention your current offered salary details / offered company name : Your Preferred Interview Date / Time:

Brief About Fractal Fractal Analytics is Leading Fortune 500 companies leverage Big Data, analytics and technology to drive smarter, faster and more accurate decisions in every aspect of their business. Fortune 500 companies recognize analytics is a competitive advantage to understand s and make better decisions. We deliver insight, innovation and impact to them through predictive analytics and visual storytelling. Role & Responsibilities: Experience of working on end-to-end data science pipeline with the ability to clearly design efficient data models, training data samples, training pipelines and inference pipelines to ensure reproducibility. Strong experience in evaluating different types of AI/ML outputs and models (recommender systems, similarity scoring, classification and regression). Should be able to break down complex business problems into sub-tasks that can be solved with AI/ML to enable decision making at scale. Should have good grasp on statistical concepts and empirical methods that drive post-modeling decisions like sorting, ranking , selection etc. Should have good experience in converting PoCs and experimented models into production grade AIML systems , have the ability to collaborate effectively with ML engineering and MLOPs teams to take AI/ML models to production, build and serve models through APIs and support integration of AI/ML models into web-aps. Ability to lead mid-sized teams, plan project tracks around AI/ML and data science and balance delegation and hands-on development. Experience in taking first principles approach to solving data science problems, understand and communicate data requirements to data engineering teams and explain model outputs to business users. Ability and experience in engaging business users to understand requirements and translate them into technical data science problems. Be exceptional at communicating and translating model algorithms and their outputs to non-technical users and stakeholders. Fluent in agile ways of working and agile project management practices. Should be comfortable to create efficient user stories, and other agile project artifacts.

Job Summary We are seeking a detail-oriented and technically proficient GenAI Tester to validate and ensure the quality of Generative AI solutions. This role involves testing AI models, APIs, and integrated systems with a focus on Python-based automation, FastAPI endpoints, and advanced GenAI components such as Agentic AI and Vector Databases. Key Responsibilities - Design and execute test plans for GenAI applications and services. - Develop automated test scripts using Python for FastAPI endpoints and AI workflows. - Validate the functionality and performance of Agentic AI systems and Vector DB integrations. - Collaborate with developers and data scientists to understand model behavior and expected outcomes. - Perform regression, integration, and performance testing on GenAI components. - Document test cases, results, and defects with clarity and precision. - Ensure secure and ethical testing practices in alignment with organizational standards. Required Qualifications - Bachelors degree in Computer Science, Engineering, or related field. - 3+ years of experience in software testing, preferably in AI/ML environments. - Proficiency in Python and FastAPI for test automation. - Understanding of Generative AI concepts including Agentic AI and Vector Databases. - Experience with API testing tools and frameworks. - Strong analytical and problem-solving skills. Preferred Qualifications - Experience with MLOps and AI model lifecycle testing. - Knowledge of secure architecture and authentication/authorization mechanisms. - Familiarity with cloud-based testing environments (AWS, Azure, GCP). - Certifications in software testing or AI quality assurance. Why Join Us? Join a forward-thinking team dedicated to building and validating cutting-edge Generative AI solutions. Youll have the opportunity to work with innovative technologies, collaborate with top-tier professionals, and contribute to the development of secure and high-performing AI systems.

#Hiring who have experience in Pyspark, Python, GCP, Airflow, BigQuery/SQL #Company- US-Based an MNC #Location- Hyderabad/Chennai #Work mode- Hybrid & Gnrl shift #Budget- 16LPA Maxx Taslim DM -7050041829 anishaglobal4@gmail.com

Role & responsibilities 3+ years of professional software development experience with strong proficiency in Python . Hands-on experience building applications that interact with or utilize Generative AI models (e.g., Large Language Models - LLMs). Familiarity with key Generative AI concepts like prompt engineering, Retrieval-Augmented Generation (RAG). Experience with relevant Python libraries and frameworks for application development (e.g., Flask, FastAPI, Streamlit, LangChain, Hugging Face Transformers). Solid understanding of software engineering principles, including API design, data structures, and algorithms. Experience with version control systems (e.g., Git). Ability to work effectively in a collaborative team environment.

skills in Python, with experience in ML libraries like Tensor Flow, PyTorch, Scikit-learn, XGBoost,AWS, Azure, or GCP and cloud-native ML tools (SageMaker, Vertex AI, Azure ML)Docker, Kubernetes,MLOps, model monitoring, Spark, Hadoop, Hive

The position of Gen AI / AI Engineer (Mid-Level) in Hyderabad requires a candidate with at least 2 years of experience in developing and deploying AI/ML solutions, focusing particularly on Generative AI and RAG (Retrieval-Augmented Generation) architectures. As an AI Engineer, you will be involved in working with cutting-edge models, fine-tuning, and integrating systems to create scalable AI products. Your responsibilities will include fine-tuning and optimizing Large Language Models (LLMs) and generative models for both text and image data. You will also be responsible for designing and implementing RAG pipelines that incorporate knowledge bases, developing APIs, microservices, and scalable AI pipelines, collaborating with MLOps teams for production deployment, and staying updated on the latest AI trends to apply innovative techniques effectively. The ideal candidate should possess expertise in Python programming language, PyTorch or TensorFlow frameworks, Generative AI tools such as OpenAI, Anthropic, LLaMA, RAG architecture, Natural Language Processing (NLP), Computer Vision, API development, MLOps practices, and experience working with Cloud Platforms like AWS, Azure, or GCP. Qualifications for this role include a Bachelor's degree in Computer Science or a related field, a minimum of 2 years of experience in AI/ML with a focus on GenAI and RAG, and hands-on experience in deploying models at a production level. If you are enthusiastic about contributing to the development of next-generation AI solutions, we encourage you to apply for this exciting opportunity.,

As a talented Full Stack Developer with expertise in Generative AI and Natural Language Processing, you will be a key member of our team, contributing to the design, development, and scaling of cutting-edge LLM and Generative AI applications to enhance user experiences. Your responsibilities will include developing backend logic and intelligent workflows using pre-trained AI models such as large language models (LLMs) and natural language understanding (NLU) engines. You will integrate and operationalise NLP and Generative AI models in production environments, including speech processing pipelines like automatic speech recognition (ASR) and text-to-speech (TTS) technologies. Applying techniques such as LLM fine-tuning, prompt engineering, and Retrieval-Augmented Generation (RAG) will be crucial for enhancing AI system performance. Moreover, you will design and deploy scalable full-stack solutions supporting AI-driven applications, working with various data sources to enable contextual AI retrieval and responses. Utilising cloud platforms like AWS/Azure effectively for hosting, managing, and scaling AI-enabled services will also be part of your role. If you are passionate about combining full-stack development with AI and LLM technologies to create innovative text and voice applications, we look forward to hearing from you. Qualifications: - 3+ years of hands-on experience in full-stack application development with a strong understanding of frontend and backend technologies. - 12 years of proven experience in designing and implementing AI-driven conversational systems. - Deep knowledge of integrating Speech-to-Text (STT) and Natural Language Processing (NLP) components into production-ready systems. Nice-to-Have Skills: - Exposure to MLOps practices, including model deployment, monitoring, lifecycle management, and performance optimization in production environments. What You'll Get: - Opportunity to work on one of the most advanced AI systems. - A high-performing, fast-paced startup culture with a deep tech focus.,

You are a skilled Architect specializing in AIOps & MLOps Operations, responsible for supporting and enhancing the automation, scalability, and reliability of AI/ML operations across the enterprise. Your role involves deploying AI/ML models, ensuring continuous monitoring, and implementing self-healing automation to enhance system performance, minimize downtime, and improve decision-making with real-time AI-driven insights. Supporting and maintaining AIOps and MLOps programs is a key responsibility, ensuring alignment with business objectives, data governance standards, and enterprise data strategy. You will assist in implementing real-time data observability, monitoring, and automation frameworks to enhance data reliability, quality, and operational efficiency. Your role will also involve contributing to the development of governance models and execution roadmaps, driving efficiency across data platforms such as Azure, AWS, GCP, and on-prem environments. It is essential to ensure seamless integration of CI/CD pipelines, data pipeline automation, and self-healing capabilities across the enterprise. Collaboration with cross-functional teams to support the development and enhancement of next-generation Data & Analytics (D&A) platforms will be part of your responsibilities. Additionally, you will assist in managing the people, processes, and technology involved in sustaining Data & Analytics platforms, driving operational excellence and continuous improvement. Moreover, you will support Data & Analytics Technology Transformations by ensuring proactive issue identification and the automation of self-healing capabilities across the PepsiCo Data Estate. Your role will involve implementing AIOps strategies for automating IT operations using Azure Monitor, Azure Log Analytics, and AI-driven alerting. You will deploy Azure-based observability solutions to enhance real-time system performance monitoring and enable AI-driven anomaly detection and root cause analysis. Contribution to developing self-healing and auto-remediation mechanisms using Azure Logic Apps, Azure Functions, and Power Automate will be part of your responsibilities. Supporting ML lifecycle automation using Azure ML, Azure DevOps, and Azure Pipelines for CI/CD of ML models is also essential. You will assist in deploying scalable ML models with Azure Kubernetes Service, Azure Machine Learning Compute, and Azure Container Instances while automating feature engineering, model versioning, and drift detection. Collaboration with various teams to align AIOps/MLOps strategies with enterprise IT goals is an important aspect of the role. You will work closely with business stakeholders and IT leadership to implement AI-driven insights and automation for enhancing operational decision-making. Tracking and reporting AI/ML operational KPIs and ensuring adherence to Azure Information Protection and data security policies will also be part of your responsibilities. In summary, your role as an Architect - AIOps & MLOps Operations will involve supporting, enhancing, and automating AI/ML operations across the enterprise, ensuring operational excellence, and continuous improvement.,

As the MLOps Engineering Director at Horizontal Data Science Enablement Team within SSO Data Science, you will play a crucial role in solving MLOps challenges, overseeing the Databricks platform, building CI/CD pipelines, and leading best practices. Your responsibilities will include the administration, configuration, and maintenance of Databricks clusters and workspaces. It will be essential to continuously monitor clusters for high workloads or excessive costs and alert relevant stakeholders promptly to maintain overall cluster health. Implementing and managing security protocols, including access controls and data encryption, to adhere to Mastercard standards will be a key aspect of your role. You will be responsible for integrating various data sources into Databricks to ensure seamless data flow and consistency. Resolving issues related to Databricks infrastructure, providing support to users and stakeholders, maintaining documentation of configurations, processes, and best practices, and leading security and architecture reviews will also be part of your responsibilities. Bringing MLOps expertise to the table will involve activities such as model monitoring, feature catalog/store, model lineage maintenance, and CI/CD pipeline management. You will also own and maintain MLOps solutions, build LLMOps pipelines, and manage a small team of MLOps engineers. To excel in this role, a Master's degree in computer science or a related field, strong experience with Databricks, cloud technologies, MLOps solutions like MLFlow, and hands-on experience in CI/CD tools are required. Additionally, you should have experience in data analysis, data observability, data ingestion, data integration, and system engineering. Strong coding skills in Python or other languages like Java and C++, along with a systematic problem-solving approach and effective communication skills, will be essential. Experience with SQL tuning, automation, data observability, and supporting highly scalable systems can set you apart. Operating in a 24x7 environment and being self-motivated to creatively solve software problems will be valuable assets in this role. As part of your corporate security responsibility, you are expected to abide by Mastercard's security policies, ensure information confidentiality and integrity, report any security violations, and complete mandatory security training.,

You are an experienced professional with over 10 years of total experience, seeking a new opportunity to showcase your expertise in Python, LLM integration, and GenAI development workflows. Your strong knowledge in prompt engineering, vector databases, retrieval-augmented generation (RAG), and toolchains sets you apart. You have hands-on experience with Agentic AI and Open AI, as well as agent frameworks like LangChain Agents, Semantic Kernel, Haystack, or custom-built agents. Your proven track record includes leading LLM/GenAI projects from Proof-of-Concept to Production, showcasing your deep understanding of modern data workflows including ingestion, transformation, cataloguing, validation, and analytics. Collaboration is key for you, as you have the ability to work across engineering, product, and governance teams. Experience with enterprise data products, MLOps, or DataOps platforms, as well as familiarity with governance workflows and metadata-driven automation, are part of your skill set. Your responsibilities will include understanding clients" business use cases and technical requirements to create elegant technical designs, mapping decisions with requirements, identifying the best solutions, and defining guidelines and benchmarks for NFR considerations during project implementation. You will be responsible for writing and reviewing design documents, reviewing architecture and design, ensuring best practices are followed, and developing overall solutions for functional and non-functional requirements. To excel in this role, you should have a Bachelor's or Master's degree in computer science, Information Technology, or a related field. Your excellent communication and collaboration skills will be essential as you resolve issues raised during code/review and carry out POCs to validate suggested designs and technologies. Join us at Nagarro and be part of a dynamic and non-hierarchical work culture where your expertise will be valued and your contributions will make a difference.,

The Artificial Intelligence/Machine Learning Engineer position at CDM Smith involves collaborating with the Data Technology group within the Digital Engineering Solutions team to drive strategic Architecture, Engineering, and Construction (AEC) initiatives using advanced data technologies and analytics. By leveraging artificial intelligence (AI) and machine learning (ML), the individual will play a crucial role in providing actionable business insights and robust solutions for AEC professionals and client outcomes. The focus will be on utilizing advanced analytics, data science, and AI/ML to give the business a competitive edge, including understanding and managing data, architecting & engineering data for self-serve Business Intelligence (BI) and Business Analytics (BA) opportunities. As an AI/ML Engineer at CDM Smith, you will be responsible for applying state-of-the-art algorithms and techniques such as deep learning, NLP, computer vision, and time-series analysis for domain-specific use cases within the AEC domain. You will analyze large datasets to identify patterns and trends, participate in AI model testing and validation, and optimize AI/ML workflows through MLOps practices. Collaboration with Data Engineers, Data Scientists, and other stakeholders to design and implement end-to-end AI/ML solutions will be a key aspect of this role. In addition to technical responsibilities, the position requires staying updated on the latest developments in AI/ML technologies and best practices, contributing to the development of documentation, standards, and best practices for data technology, and effectively communicating complex technical concepts to both technical and non-technical audiences. Strong problem-solving, critical thinking, and communication skills are essential for successfully executing highly complex projects and generating innovative solutions to improve business processes. To qualify for this role, you should have a Bachelor's degree and 1-2 years of related experience. Equivalent additional related experience will be considered in lieu of a degree. Basic experience with building and deploying machine learning models using frameworks like TensorFlow, PyTorch, or Scikit-learn, familiarity with cloud-based AI/ML services, programming languages such as R, Python, or Scala, and knowledge of MLOps practices are required. Understanding of data privacy, security, and ethical AI principles is essential to ensure compliance with relevant standards. This position does not require any travel. Please note that CDM Smith may conduct background checks, including criminal, employment, education, and drug testing, for designated positions. Employment will be contingent upon the successful completion of these checks.,

As an AI Research Scientist, your role will involve developing the overarching technical vision for AI systems that cater to both current and future business needs. You will be responsible for architecting end-to-end AI applications, ensuring seamless integration with legacy systems, enterprise data platforms, and microservices. Collaborating closely with business analysts and domain experts, you will translate business objectives into technical requirements and AI-driven solutions. Working in partnership with product management, you will design agile project roadmaps that align technical strategy with market needs. Additionally, you will coordinate with data engineering teams to guarantee smooth data flows, quality, and governance across various data sources. Your responsibilities will also include leading the design of reference architectures, roadmaps, and best practices for AI applications. You will evaluate emerging technologies and methodologies, recommending innovations that can be integrated into the organizational strategy. Identifying and defining system components such as data ingestion pipelines, model training environments, CI/CD frameworks, and monitoring systems will be crucial aspects of your role. Leveraging containerization (Docker, Kubernetes) and cloud services, you will streamline the deployment and scaling of AI systems. Implementing robust versioning, rollback, and monitoring mechanisms to ensure system stability, reliability, and performance will also be part of your duties. Project management will be a key component of your role, overseeing the planning, execution, and delivery of AI and ML applications within budget and timeline constraints. You will be responsible for the entire lifecycle of AI application development, from conceptualization and design to development, testing, deployment, and post-production optimization. Enforcing security best practices throughout each phase of development, with a focus on data privacy, user security, and risk mitigation, will be essential. Furthermore, providing mentorship to engineering teams and fostering a culture of continuous learning will play a significant role in your responsibilities. In terms of mandatory technical and functional skills, you should possess a strong background in working with or developing agents using langgraph, autogen, and CrewAI. Proficiency in Python, along with robust knowledge of machine learning libraries such as TensorFlow, PyTorch, and Keras, is required. You should also have proven experience with cloud computing platforms (AWS, Azure, Google Cloud Platform) for building and deploying scalable AI solutions. Hands-on skills with containerization (Docker), orchestration frameworks (Kubernetes), and related DevOps tools like Jenkins and GitLab CI/CD are necessary. Experience using Infrastructure as Code (IaC) tools such as Terraform or CloudFormation to automate cloud deployments is essential. Additionally, proficiency in SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra) and expertise in designing distributed systems, RESTful APIs, GraphQL integrations, and microservices architecture are vital for this role. Knowledge of event-driven architectures and message brokers (e.g., RabbitMQ, Apache Kafka) is also required to support robust inter-system communications. Preferred technical and functional skills include experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack) to ensure system reliability and operational performance. Familiarity with cutting-edge libraries such as Hugging Face Transformers, OpenAI's API integrations, and other domain-specific tools is advantageous. Experience in large-scale deployment of ML projects, along with a good understanding of DevOps/MLOps/LLM Ops and training and fine-tuning of Large Language Models (SLMs) like PALM2, GPT4, LLAMA, etc., is beneficial. Key behavioral attributes for this role include the ability to mentor junior developers, take ownership of project deliverables, contribute to risk mitigation, and understand business objectives and functions to support data needs. If you have a Bachelor's or Master's degree in Computer Science, certifications in cloud technologies (AWS, Azure, GCP), and TOGAF certification (good to have), along with 11 to 14 years of relevant work experience, this role might be the perfect fit for you.,

Qualcomm India Private Limited is looking for a highly skilled and experienced MLOps Engineer to join their team and contribute to the development and maintenance of their ML platform both on premises and AWS Cloud. As a MLOps Engineer, your responsibility will include architecting, deploying, and optimizing the ML & Data platform supporting the training of Machine Learning Models using NVIDIA DGX clusters and the Kubernetes platform. Your expertise in AWS services such as EKS, EC2, VPC, IAM, S3, and EFS will be crucial for ensuring the smooth operation and scalability of the ML infrastructure. You will collaborate with cross-functional teams, including data scientists, software engineers, and infrastructure specialists, to ensure the smooth operation and scalability of the ML infrastructure. Your expertise in MLOps, DevOps, and knowledge of GPU clusters will be vital in enabling efficient training and deployment of ML models. Your responsibilities will include architecting, developing, and maintaining the ML platform, designing and implementing scalable infrastructure solutions for NVIDIA clusters on premises and AWS Cloud, collaborating with data scientists and software engineers to define requirements, optimizing platform performance and scalability, monitoring system performance, implementing CI/CD pipelines, maintaining monitoring stack using Prometheus and Grafana, managing AWS services, implementing logging and monitoring solutions, staying updated with the latest advancements in MLOps, distributed computing, and GPU acceleration technologies, and proposing enhancements to the ML platform. Qualcomm is looking for candidates with a Bachelor's or Master's degree in Computer Science, Engineering, or a related field, proven experience as an MLOps Engineer or similar role with a focus on large-scale ML and/or Data infrastructure and GPU clusters, strong expertise in configuring and optimizing NVIDIA DGX clusters, proficiency in using the Kubernetes platform and related technologies, solid programming skills in languages like Python, Go, experience with relevant ML frameworks, in-depth understanding of distributed computing and GPU acceleration techniques, familiarity with containerization technologies and orchestration tools, experience with CI/CD pipelines and automation tools for ML workflows, experience with AWS services and monitoring tools, strong problem-solving skills, excellent communication, and collaboration skills. Qualcomm is an equal opportunity employer and is committed to providing reasonable accommodations to support individuals with disabilities during the hiring process. If you are interested in this role or require more information, please contact Qualcomm Careers.,

At Improzo, we are dedicated to improving life by empowering our customers through quality-led commercial analytical solutions. Our team of experts in commercial data, technology, and operations collaborates to shape the future with leading Life Sciences clients and carefully chosen peers. People are at the heart of our success, and we uphold our CARE values framework, prioritizing customer needs, pursuing innovation, fostering respect, and maintaining a focus on quality-led execution. As a Data Scientist in Pune at Improzo, your role involves driving insights for pharma clients using advanced ML, Gen AI, and LLMs on complex healthcare data. You will be optimizing Pharma commercial strategies and improving patient outcomes through various analytical techniques. Your responsibilities will include engaging with client stakeholders to understand challenges and strategic objectives, exploring and preparing complex datasets from various sources, developing statistical models and machine learning algorithms, analyzing promotional effectiveness and patient adherence, utilizing generative AI and LLM solutions, transforming analytical findings into actionable recommendations, collaborating with cross-functional teams, and supporting the entire data science lifecycle. To qualify for this role, you should have a Master's or Ph.D. in a related quantitative field, at least 4 years of experience as a Data Scientist, a solid understanding of pharmaceutical commercial operations, experience with real-world patient data and patient journeys, strong programming skills in Python and/or R, expertise in SQL and data visualization tools, familiarity with cloud platforms and big data technologies, knowledge of NLP techniques and LLMs, experience with MLOps practices and tools, and an understanding of industry regulations and compliance requirements. Additionally, excellent communication, presentation, interpersonal skills, attention to detail, client centricity, ability to work independently and as part of a team, and strong leadership skills are essential. Join us at Improzo for a competitive salary and benefits package, the opportunity to work on cutting-edge Analytics projects, a collaborative work environment, and professional development opportunities. If you are passionate about data manipulation, analytics, generative AI, commercial pharma, MLOps, and have the necessary skills and experience, we look forward to having you on our team.,

As an Artificial Intelligence Specialist at Gen AI, you will be responsible for driving customer conversations, understanding customer requirements, creating Gen AI solution architectures, and developing customer proposals and RFP responses. You will guide solution engineers in creating Gen AI POCs and solutions for various industry verticals. Your role will involve staying updated on the latest technology developments, industry best practices, and incorporating them into Gen AI applications. Additionally, you will design and deploy Proof of Concepts (POCs) and Points of View (POVs) across different industry verticals to showcase the potential of Generative AI applications. To qualify for this role, you should have at least 8 years of experience in software development, with a minimum of 3 years of experience in Generative AI solution development. A bachelor's degree or higher in Computer Science, Software Engineering, or related fields is required. You should be adept at critical thinking, logical reasoning, and have a strong ability to learn new industry domains quickly. Being a team player who can deliver under pressure is essential. Furthermore, you should have experience with cloud technologies such as Azure, AWS, or GCP, as well as a good understanding of NVIDIA or similar technologies. A solid appreciation of AI/ML concepts and sound design principles is necessary for this role. In terms of required skills, you should be extremely dynamic and enthusiastic about technology. Development experience with languages like C++, Java, JavaScript, HTML, C#, Python, or node.js is preferred. You should be able to adapt quickly to new challenges and evolving technology stacks. Excellent written and verbal communication skills in English are essential, along with strong analytical and critical thinking abilities. A customer-focused attitude, initiative-taking, self-driven nature, and the ability to learn quickly are also important qualities for this role. Knowledge of Python, ML Algorithms, Statistics, source code maintenance, versioning tools, Object-Oriented Programming Concepts, debugging, and analytical skills is required. Preferred skills for this position include at least 5 years of experience in ML development and MLOps. Strong programming skills in Python, knowledge of ML, Data, and API libraries, and expertise in creating end-to-end data pipelines are advantageous. Experience with ML models, ModelOps/MLOps, AutoML, AI Ethics, Trust, Explainable AI, and popular ML frameworks like SparkML, TensorFlow, scikit-learn, XGBoost, H2O, etc., is beneficial. Familiarity with working in cloud environments (AWS, Azure, GCP) or containerized environments (Mesos, Kubernetes), interest in understanding functional and industry business challenges, and knowledge of IT industry and GenAI use cases in insurance processes are preferred. Expertise in Big Data and Data Modeling is also desirable for this role.,

As an AI Automation Solution Architect/Lead with a background in infrastructure, you will play a crucial role in designing, leading, and implementing advanced AI-driven automation solutions to enhance our infrastructure, operations, and business processes. Your responsibilities will include creating scalable, secure, and high-performing automation initiatives that leverage AI/ML technologies and enterprise-grade IT infrastructure. You will lead the design and architecture of AI-powered automation solutions, focusing on infrastructure automation, AIOps, intelligent process automation, and self-healing systems. Your role will involve defining technical roadmaps, blueprints, and reference architectures that align with enterprise architecture and business objectives. Additionally, you will evaluate and select AI/ML models, tools, platforms, and infrastructure technologies to meet solution requirements effectively. In this position, you will provide technical leadership and mentorship to development, MLOps, and infrastructure teams, guiding them on best practices for AI automation, infrastructure as code, and cloud-native architectures. You will drive the adoption of modern engineering practices, advise stakeholders on the feasibility of AI automation technologies, and identify opportunities to leverage AI and automation for operational efficiency and innovation. Collaboration with infrastructure teams, clear communication of technical concepts to diverse audiences, and the management of vendor relationships will be essential aspects of your role. You will have the opportunity to contribute to the development of organizational standards, policies, and governance frameworks for AI automation, ensuring alignment with industry best practices. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field, along with 18+ years of experience in IT, including a minimum of 5 years in a solution architecture or lead role focused on automation, infrastructure, or cloud. Proficiency in cloud platforms, infrastructure components, Infrastructure as Code tools, and programming languages commonly used in AI/ML and automation is required. Strong communication, presentation, and interpersonal skills are essential for success in this position. Preferred qualifications include experience with specific AI automation platforms, certifications in cloud architecture, understanding of ITIL, DevOps, and Agile methodologies, and familiarity with enterprise-level security practices and compliance frameworks. In this role, you will have the opportunity to work with cutting-edge AI and automation technologies, collaborate in an innovative work environment, receive a competitive salary and benefits package, and access professional development and growth opportunities. Your contributions will have a significant impact on the company's operational efficiency and strategic direction.,

As a Senior/Lead Data Scientist at our organization, you will be a crucial member of our AI/ML team, bringing your expertise in Machine Learning and Deep Learning to design, develop, and deploy AI/ML models for Computer Vision and Generative AI (GenAI) use cases. With a minimum of 4 years of hands-on experience, you will leverage your skills in Computer Vision tasks such as object detection, image segmentation, and OCR, along with a strong programming background in Python and frameworks like PyTorch, TensorFlow, OpenCV, and Transformers. Your responsibilities will include collaborating with product and engineering teams to integrate models into scalable pipelines and applications, managing the complete ML lifecycle using MLOps practices, analyzing large-scale datasets, and preparing them for model training and validation. Additionally, you will work with Azure Machine Learning Services for training, inference, and model management, ensuring high-quality, production-grade ML code and documentation of technical designs and decision-making processes. To excel in this role, you should have a good understanding of MLOps concepts, model deployment, and lifecycle management, as well as experience with cloud platforms, preferably Azure ML, for scalable model training and deployment. Your familiarity with data labeling tools, synthetic data generation, and model interpretability will be valuable assets in this position. Strong problem-solving, debugging, and communication skills are essential for effectively collaborating with cross-functional teams. While not mandatory, experience with NLP, multimodal learning, or 3D computer vision, as well as familiarity with containerization tools like Docker and Kubernetes, would be beneficial. Exposure to building end-to-end ML pipelines using tools like MLflow or DVC, and working in agile development environments, will also be advantageous. If you possess a Bachelors or Masters degree in Computer Science, Electrical Engineering, Data Science, or a related field, and are looking to contribute your expertise to a dynamic team focused on leveraging AI/ML technologies to drive growth and innovation, we encourage you to apply for this exciting opportunity.,

You are a seasoned Staff Data Scientist with over 8 years of experience in Data Science/ML, specializing in Generative AI, Large Language Models (LLMs), and deep learning. Your role at PhysicsWallah involves leading and driving innovation in Generative AI, LLMs, Retrieval-Augmented Generation (RAG), Reinforcement Learning, and model fine-tuning. You will collaborate closely with cross-functional teams to create next-gen AI solutions that enhance content generation, adaptive learning, and personalized experiences for millions of learners. As a Staff Data Scientist at PhysicsWallah, your key responsibilities include designing and developing advanced AI/ML solutions using LLMs, RAG, and RL techniques, fine-tuning and customizing models for PW-specific education scenarios, building scalable pipelines for training and deployment of GenAI models, integrating models into real-world applications, conducting experiments and testing to enhance model performance, staying updated on GenAI trends to influence internal strategies, and mentoring junior data scientists while promoting best practices within the AI team. You should possess expertise in Retrieval-Augmented Generation (RAG) architectures, transforming transformer-based models like BERT, GPT, LLaMA, and Mistral, hands-on experience in Reinforcement Learning with a focus on RLHF or similar approaches, proficiency in Python and ML frameworks such as PyTorch, TensorFlow, HuggingFace, LangChain, and Ray, strong knowledge of cloud platforms like AWS/GCP and MLOps for scalable AI model deployment, a track record of deploying ML models in production environments, excellent communication skills, and the ability to work in cross-functional environments. Preferred qualifications for this role include published papers, patents, or contributions to open-source GenAI projects, experience in edtech or adaptive learning platforms, and exposure to vector databases like FAISS, Pinecone, and Weaviate, as well as semantic search systems. Join PhysicsWallah and be part of a mission-driven organization that aims to make quality education accessible to all. You will have the opportunity to work on cutting-edge GenAI challenges with significant real-world impact in a collaborative and fast-paced environment that offers immense learning opportunities. Shape the future of education with GenAI at PhysicsWallah by applying now.,

You will be responsible for building curated enterprise-grade solutions for GenAI application deployment at a production scale for clients. This role demands a solid understanding and hands-on skills in GenAI application deployment, encompassing development and engineering skills. You will need to possess expertise in data ingestion, selecting the appropriate LLMs, implementing simple and advanced RAG, guardrails, prompt engineering for optimization, traceability, security, LLM evaluation, observability, and deployment at scale on cloud or on-premise. It is essential for candidates to demonstrate knowledge of agentic AI frameworks due to the rapid evolution of this space. Strong background in ML with engineering skills is highly preferred for the LLMOps role. You should have 3 - 5 years of experience working on ML projects, involving business requirement gathering, model development, training, deployment at scale, and monitoring model performance for production use cases. Proficiency in Python, NLP, Data Engineering, Langchain, Langtrace, Langfuse, RAGAS, AgentOps (optional) is crucial. Experience with proprietary and open-source large language models, LLM fine-tuning, creating distilled models from hosted LLMs, and building data pipelines for model training is required. You should also have experience in model performance tuning, RAG, guardrails, prompt engineering, evaluation, and observability. Prior experience in GenAI application deployment on cloud and on-premises at scale for production, creating CI/CD pipelines, working with Kubernetes, and deploying AI services on at least one cloud platform such as AWS, GCP, or Azure is necessary. Proficiency in creating workable prototypes using Agentic AI frameworks like CrewAI, Taskweaver, AutoGen, and light-weight UI development using streamlit or chainlit (optional) is beneficial. Desired experience with open-source tools for ML development, deployment, observability, and integration is an added advantage. A background in DevOps and MLOps will be a plus. You should be familiar with collaborative code versioning tools like GitHub/GitLab and possess excellent communication and presentation skills. A degree in Computer Science, related technical field, or equivalent is required. If you are someone who thrives in a dynamic environment and enjoys collaborating with enthusiastic individuals, this opportunity is perfect for you.,