146 Ml Ops Jobs

We are CirrusLabs . Our vision is to become the world's most sought-after niche digital transformation company that helps customers realize value through innovation. Our mission is to co-create success with our customers, partners and community. Our goal is to enable employees to dream, grow and make things happen. We are committed to excellence. We are a dependable partner organization that delivers on commitments. We strive to maintain integrity with our employees and customers. Every action we take is driven by value. The core of who we are is through our well-knit teams and employees. You are the core of a values driven organization. You have an entrepreneurial spirit. You enjoy working as a part of well-knit teams. You value the team over the individual. You welcome diversity at work and within the greater community. You aren't afraid to take risks. You appreciate a growth path with your leadership team that journeys how you can grow inside and outside of the organization. You thrive upon continuing education programs that your company sponsors to strengthen your skills and for you to become a thought leader ahead of the industry curve. You are excited about creating change because your skills can help the greater good of every customer, industry and community. We are hiring a talented AI Architect to join our team. If you're excited to be part of a winning team, CirrusLabs ( http://www.cirruslabs.io ) is a great place to grow your career. Experience - 8 - 10 years Location - Bengaluru Mandatory skills: Python, Gen AI, traditional ML, core Data scientist, ML Ops, Agentic AI Position Overview We are seeking an experienced AI Architect to join our dynamic team. This role combines deep technical expertise in traditional statistics, classical machine learning, and modern AI with full-stack development capabilities to build end-to-end intelligent systems. You'll work on revolutionary projects involving generative AI, large language models, and advanced data science applications. Key Responsibilities AI/ML Development & Data Science: Design, develop, and deploy machine learning models ranging from classical algorithms to deep learning for production environments Apply traditional statistical methods including hypothesis testing, regression analysis, time series forecasting, and experimental design Build and optimize large language model applications including fine-tuning, prompt engineering, and model evaluation Implement Retrieval Augmented Generation (RAG) systems for enhanced AI capabilities Conduct advanced data analysis, statistical modeling, A/B testing, and predictive analytics using both classical and modern techniques Research and prototype cutting-edge generative AI solutions Traditional ML & Statistics: Implement classical machine learning algorithms including linear/logistic regression, decision trees, random forests, SVM, clustering, and ensemble methods Perform feature engineering, selection, and dimensionality reduction techniques Conduct statistical inference, confidence intervals, and significance testing Design and analyze controlled experiments and observational studies Apply Bayesian methods and probabilistic modeling approaches Full Stack Development: Develop scalable front-end applications using modern frameworks (React, Vue.js, Angular) Build robust backend services and APIs using Python, Node.js, or similar technologies Design and implement database solutions (SQL/NoSQL) optimized for ML workloads Create intuitive user interfaces for AI-powered applications and statistical dashboards MLOps & Infrastructure: Establish and maintain ML pipelines for model training, validation, and deployment Implement CI/CD workflows for ML models using tools like MLflow, Kubeflow, or similar Monitor model performance, drift detection, and automated retraining systems Deploy and scale ML solutions using cloud platforms (AWS, GCP, Azure) Containerize applications using Docker and orchestrate with Kubernetes Collaboration & Leadership: Work closely with data scientists, product managers, and engineering teams Mentor junior engineers and contribute to technical decision-making Participate in code reviews and maintain high development standards Stay current with latest AI/ML trends and technologies Required Qualifications Experience & Education: 7-8 years of professional software development experience Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Machine Learning, Data Science, or related field 6+ years of hands-on AI/ML experience in production environments Technical Skills: Programming: Expert proficiency in Python, strong experience with JavaScript/TypeScript, R is a plus Traditional ML: Scikit-learn, XGBoost, LightGBM, classical algorithms and ensemble methods Statistics: Hypothesis testing, regression analysis, ANOVA, time series analysis, experimental design, Bayesian inference Statistical Tools: Experience with R, SAS, SPSS, or similar statistical software packages Deep Learning: TensorFlow, PyTorch, neural networks, computer vision, NLP LLM Experience: Working with GPT, Claude, Llama, or similar models; experience with fine-tuning and prompt engineering RAG Implementation: Vector databases (Pinecone, Weaviate, Chroma), embedding models, semantic search Data Science: Pandas, NumPy, statistical analysis, data visualization (Matplotlib, Plotly, Seaborn), feature engineering Full Stack: React/Vue.js, Node.js/FastAPI, REST/GraphQL APIs Databases: PostgreSQL, MongoDB, Redis, vector databases MLOps: Docker, Kubernetes, CI/CD, model versioning, monitoring tools Cloud Platforms: AWS/GCP/Azure, serverless architectures Soft Skills: Strong problem-solving and analytical thinking Excellent communication and collaboration abilities Self-motivated with ability to work in fast-paced environments Experience with agile development methodologies Preferred Qualifications Experience with causal inference methods and econometric techniques Knowledge of distributed computing frameworks (Spark, Dask) Experience with edge AI and model optimization techniques Publications in AI/ML/Statistics conferences or journals Open source contributions to ML/statistical projects Experience with advanced statistical modeling and multivariate analysis Familiarity with operations research and optimization techniques

As a Lead Software Engineer at our company, you will be responsible for designing, building, and scaling high-performance infrastructure with expertise in ML Ops, distributed systems, and platform engineering. Your key responsibilities will include: - Designing and developing scalable, secure, and reliable microservices using Golang and Python. - Building and maintaining containerized environments using Docker and orchestrating them with Kubernetes. - Implementing CI/CD pipelines with Jenkins for automated testing, deployment, and monitoring. - Managing ML workflows with MLflow to ensure reproducibility, versioning, and deployment of machine learning models. - Leveraging Temporal for orchestrating complex workflows and ensuring fault-tolerant execution of distributed systems. - Working with AWS cloud services (EC2, S3, IAM, basics of networking) to deploy and manage scalable infrastructure. - Collaborating with data science and software teams to bridge the gap between ML research and production systems. - Ensuring system reliability and observability through monitoring, logging, and performance optimization. - Mentoring junior engineers and leading best practices for ML Ops, DevOps, and system design. To be successful in this role, you should have: - Minimum 5+ years of experience. - Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. - Strong programming skills in Golang and Python. - Hands-on experience with Kubernetes and Docker in production environments. - Proven experience in microservices architecture and distributed systems design. - Good understanding of AWS fundamentals (EC2, S3, IAM, networking basics). - Experience with MLflow for ML model tracking, management, and deployment. - Proficiency in CI/CD tools (preferably Jenkins). - Knowledge of Temporal or similar workflow orchestration tools. - Strong problem-solving and debugging skills in distributed systems. - Excellent communication and leadership skills with experience mentoring engineers.,

KONE Technology and Innovation Unit (KTI) is where the magic happens at KONE. It's where we combine the physical world - escalators and elevators - with smart and connected digital systems. We are changing and improving the way billions of people move within buildings every day. We are on a mission to expand and develop new digital solutions that are based on emerging technologies. KONE's vision is to create the Best People Flow experience by providing ease, effectiveness and experiences to our customers and users. In line with our strategy, Sustainable Success with Customers, we will focus on increasing the value we create for customers with new intelligent solutions and embed sustainability even deeper across all of our operations. By closer collaboration with customers and partners, KONE will increase the speed of bringing new services and solutions to the market. R&D unit in KTI is responsible for developing digital services at KONE. It's the development engine for our Digital Services such as , and . We are looking for Cloud Automation Architect with strong expertise in Automation on AWS cloud, UI, API, Data and ML Ops . The ideal candidate will bring hands-on technical leadership, architect scalable automation solutions, and drive end-to-end solution design for enterprise-grade use cases. You will collaborate with cross-functional teams including developers, DevOps engineers, product owners, and business stakeholders to deliver automation-first solutions. Role description: Solution Architecture & Design Architect and design automation solutions leveraging Cloud services and data management Define E2E architecture spanning cloud infrastructure, APIs, UI, and visualization layers Translate business needs into scalable, secure, and cost-effective technical solutions. Automation on Cloud Lead automation initiatives across infrastructure, application workflows, and data pipelines Implement operations use cases using Data Visualization and Cloud Automation Optimize automation for cost, performance, and security UI & API Integration Design and oversee development of APIs and microservices to support automation Guide teams on UI frameworks (React/Angular) for building dashboards and portals Ensure seamless integration between APIs, front-end applications, OCR and cloud services Data & ML Ops Define architecture for data ingestion, transformation, and visualization on AWS. Work with tools like Amazon QuickSight, Power BI to enable business insights Establish ML Ops best practices for data-driven decision-making Architect and implement end-to-end MLOps pipelines for training, deployment, and monitoring ML models. Use AWS services like SageMaker, Step Functions, Lambda, Kinesis, Glue, S3, Redshift for ML workflows. Establish best practices for model versioning, reproducibility, CI/CD for ML, and monitoring model drift. Team leading and Collaboration Mentor engineering teams on cloud-native automation practices Collaborate with product owners to prioritize and align technical solutions with business outcomes Drive POCs and innovation initiatives for automation at scale Requirements: 8-10 years of experience in cloud architecture, automation, and solution design Deep expertise in Python for automation Use cases and understanding of ML Ops Experience with data engineering & visualization tools Knowledge of UI frameworks (React, Angular, Vue) for portals and dashboards Expertise in AWS Cloud services for compute, data, and ML workloads Strong understanding of security, IAM, compliance, and networking in AWS Hands-on experience with MLOps pipelines (model training, deployment, monitoring). Read more on

Expert on MLOps, Model lifecycle + Python + PySpark + GCP (BigQuery, Dataproc & Airflow), CI/CD Call or Watsapp (ANUJ - 8249759636) for more details.

Data Science Senior Advisor Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods and models. Whats more, we are in collaboration with leading academics, industry experts and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data. Join us to do the best work of your career and make a profound social impact as a Data Science Senior Advisor on our Pricing Analytics Team under Client Solutions Group located in Bangalore . What youll achieve As a Data Science Senior Advisor, you will be responsible for contributing to business strategy and influence decision making based on information gained from deep dive analysis. You will produce actionable and compelling recommendations by interpreting insights from complex data sets. You will design processes to consolidate and examine unstructured data to generate actionable insights. You will also partner with business leaders, engineers and industry experts to construct predictive models, algorithms and probability engines. You will: •Collaborate with internal and external teams to understand customer requirements •Develop and apply a broad range of techniques and theories from statistics, machine learning, and business intelligence to deliver actionable business insights •Develop and drive testing of algorithms efficacy for differing analytical use-cases •Performs end-to-end steps involved in model development while establishing subject-matter expertise •Work with the academic and business community to develop new techniques and to contribute to research in the area of large databases Take the first step towards your dream career Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role: Essential Requirements •8 to 12 years of related experience •Solid statistical skills. ML exp, LLM models •Solid Python Programming •Good understanding of business environment and industry trends •Good communication and problem-solving skills and being customer focused Desirable Requirements •Bachelor’s degree •Ability to act as a coach to the team •Strong product/technology/industry knowledge

Role Overview: You will be joining as a Senior AI Architect in the Office of the CTO, where you will play a crucial role in designing, developing, and deploying AI and Machine Learning solutions using Python. Your primary focus will be to collaborate with enterprise customers to address critical business challenges by leveraging Azure's advanced AI capabilities. Key Responsibilities: - Lead hands-on design and development efforts using Python to create robust, scalable AI/ML solutions - Work closely with enterprise customers to strategize and implement AI-driven solutions leveraging Azure AI services - Translate complex requirements into practical technical solutions - Develop end-to-end prototypes, including data ingestion, processing, and model deployment using Azure platform components - Customize and optimize AI models for specific customer use cases - Integrate AI solutions with full-stack architectures, utilizing JavaScript frameworks and/or .NET ecosystems - Establish and maintain CI/CD and ML Ops pipelines for automated deployments - Explore diverse datasets to engineer features that enhance ML performance - Participate in all phases of the model lifecycle from conceptualization to continuous monitoring and improvement Qualifications Required: - Master's degree or higher, preferably with a specialization in Machine Learning, Data Science, or AI - Minimum of 10+ years experience as a technical solution architect with expertise in AI/ML development - Hands-on experience in Python development for building and deploying production-grade AI solutions - Successful delivery of cloud-native AI projects, preferably on the Azure platform - Expertise in deep-learning and Agentic AI frameworks such as Semantic Kernel, LangChain, LangGraph - Additional experience in JavaScript and/or .NET for full-stack solution design is preferred - Practical knowledge of Azure OpenAI, Azure ML, and AI Agent development frameworks - Proficiency in implementing automated deployments using Azure DevOps, GitHub, and understanding of MLOps practices - Strong communication skills to explain technical solutions clearly to diverse audiences - Analytical mindset with a focus on customer empathy and user-centric design Company Details: Microsoft's mission is to empower every individual and organization to achieve more. They value a growth mindset, innovation, collaboration, respect, integrity, accountability, and inclusiveness. They are looking for professionals who align with these core values.,

Aera Technology is the Decision Intelligence company. Our platform, Aera Decision Cloud, integrates with enterprise systems to digitize, augment, and automate decisions in real time. We deliver millions of AI-powered recommendations each year, generating significant value for some of the world's largest brands. We are seeking a Machine Learning Engineer (Support & Ops focus) to ensure our AI-powered decision systems run reliably at scale. This role is less about building models from scratch, and more about keeping production AI systems healthy, observable, and performant, while enabling Data Science teams to deliver faster. This position is also a strong career pathway into ML feature development. You will work closely with Product, Data Science, and Engineering teams, gain exposure to LLMs, Agentic AI, and advanced ML tooling, and progressively take on more responsibilities in building new ML-powered product features. Responsibilities - Monitor, troubleshoot, and maintain ML pipelines and services in production, ensuring high availability and minimal downtime. - Work closely with Data Scientists and Engineers to operationalize ML/LLM models, from development through deployment. - Build and maintain observability tools for tracking data quality, model performance, drift detection, and inference metrics. - Support LLM and Agentic AI features in production, focusing on stability, optimization, and seamless integration into the platform. - Develop and enhance internal ML tooling for faster experimentation, deployment, and feature integration. - Collaborate with Product teams to roll out new ML-driven features and improve existing ones. - Work with DevOps to improve CI/CD workflows for ML code, data pipelines, and models. - Optimize resource usage and costs for large-scale model hosting and inference. - Document workflows, troubleshooting guides, and best practices for ML systems support. About You - B.E./B.Tech in Computer Science, Engineering, or related field. - 3-5 years of experience in software engineering, ML Ops, or ML platform support. - Strong Python skills, with experience in production-grade code and automation. Experience with ML pipeline orchestration tools (Airflow, Prefect, Kubeflow, or similar). - Familiarity with containerized microservices (Docker, Kubernetes) and CI/CD pipelines. - Experience monitoring ML systems using tools like Prometheus, Grafana, ELK, Sentry, or equivalent. - Understanding of model packaging and serving frameworks (FastAPI, TorchServe, Triton Inference Server, Hugging Face Inference API). - Strong collaboration skills with cross-functional teams. Good to Have - Exposure to LLM operations (prompt engineering, fine-tuning, inference optimization). - Familiarity with Agentic AI workflows and multi-step orchestration (LangChain, LlamaIndex). - Experience with data versioning (DVC, Delta Lake) and experiment tracking (MLflow, Weights & Biases). - Knowledge of vector databases (Pinecone, Weaviate, FAISS). - Experience with streaming data (Kafka) and caching (Redis). - Skills in cost optimization for GPU workloads. - Basic understanding of system design for large-scale AI infrastructure. If you share our passion for building a sustainable, intelligent, and efficient world, you're in the right place. Established in 2017 and headquartered in Mountain View, California, we're a series D start-up, with teams in Mountain View, San Francisco (California), Bucharest and Cluj-Napoca (Romania), Paris (France), Munich (Germany), London (UK), Pune (India), and Sydney (Australia). So join us, and let's build this! Benefits Summary At Aera Technology, we strive to support our Aeranauts and their loved ones through different stages of life with a variety of attractive benefits, and great perks. In addition to offering a competitive salary and company stock options, we have other great benefits available. You'll find comprehensive medical, Group Medical Insurance, Term Insurance, Accidental Insurance, paid time off, Maternity leave, and much more. We offer unlimited access to online professional courses for both professional and personal development, coupled with people manager development programs. We believe in a flexible working environment, to allow our Aeranauts to perform at their best, ensuring a healthy work-life balance. When you're working from the office, you'll also have access to a fully-stocked kitchen with a selection of snacks and beverages.,

As a Python Developer in this position, you will be responsible for utilizing your expertise in Python programming to design and develop solutions for various projects. You should have a strong educational background in Computer Engineering with at least 10+ years of experience in the field. The role offers the flexibility of working from home on a full-time basis with a work schedule aligned with US timings. Your key responsibilities will include working on Load Balancers, Distributed Systems, Sticky Sessions, SQL and NoSQL Databases, Caching mechanisms like Redis and Memcached, and handling a large number of requests per second efficiently. Additionally, you should have experience in DevOps, Data Engineering, or ML Ops roles, along with proficiency in Terraform, cloud providers like AWS, GCP, or Azure, and containerization tools like Docker. You will be expected to have hands-on knowledge of ML experiment platforms such as MLflow, Kubeflow, Weights & Biases, as well as workflow execution frameworks like Kubeflow and Apache Airflow. A solid understanding of CI/CD principles, Git workflows, and infrastructure testing is essential for this role. Moreover, your communication skills should be excellent to collaborate effectively with Data Scientists, Software Engineers, and Security teams. In addition to a competitive salary, this position offers benefits such as cell phone reimbursement, leave encashment, paid sick time, paid time off, and Provident Fund. This is a full-time, permanent job opportunity that provides the convenience of working remotely while contributing to impactful projects.,

As a Senior AI/ML Engineer, you will be responsible for designing, developing, and continuously improving AI and machine learning solutions. Your main tasks will include ensuring the scalability, accuracy, and reliability of models, collaborating with team members, and providing technical expertise to drive success. You will be involved in various key responsibilities including model development where you will design, develop, and deploy machine learning models to address complex business problems. Data analysis is another crucial aspect where you will analyze datasets to uncover trends, patterns, and insights while ensuring data quality for model training. Algorithm optimization will also be a significant part of your role as you continuously enhance machine learning models for performance, scalability, and efficiency to meet business and technical requirements. Collaboration will be essential as you work closely with cross-functional teams to integrate machine learning models into production systems. Staying updated with the latest AI/ML trends and research, applying innovative approaches, and solutions to improve models and processes will be part of your research and innovation duties. You will also be responsible for model evaluation, tuning, automation, mentorship, documentation, performance monitoring, and ensuring ethical AI development. To qualify for this role, you should hold a Bachelors or Masters degree in Computer Science or a related field with at least 8+ years of experience in software development. Proficiency in Machine Learning (Supervised, Unsupervised, and Reinforcement Learning), programming languages like Python, TensorFlow, PyTorch, and cloud platforms such as AWS/Azure/GCP is required. Experience with SQL / NoSQL databases, Natural Language Processing (NLP), Design patterns, Metrics, Model Deployment metrics evaluation, and familiarity with ML OPS and Agile/Scrum methodologies are also desirable. Strong problem-solving, debugging skills, excellent communication, interpersonal skills, and the ability to work effectively in a collaborative team environment are essential for this role.,

You will be part of a globally renowned company, dunnhumby, the leader in Customer Data Science, dedicated to empowering businesses to excel in the modern data-driven economy with a strong focus on prioritizing the Customer First approach. The company's mission revolves around enabling businesses to evolve and advocate for their Customers by leveraging deep expertise in retail, catering to businesses worldwide across various industries. As an Engineering Manager with ML Ops expertise, you will lead a team of engineers in developing innovative products aimed at assisting Retailers in enhancing their Retail Media business, ultimately driving maximum ad revenue and scalability. Your role will involve crucial responsibilities such as designing and delivering high-quality software solutions, mentoring team members, contributing to system architecture, and ensuring adherence to engineering best practices. Your primary focus will be on ensuring operational efficiency and delivering valuable solutions by leading and developing a team of Big Data and MLOps engineers. You will drive best practices in software development, data management, and model deployment, emphasizing robust technical design to ensure secure, scalable, and efficient solutions. Additionally, you will engage in hands-on development to address complex challenges, collaborate across teams, keep stakeholders informed about progress, risks, and opportunities, and stay updated on advancements in AI/ML technologies to drive their application effectively. In terms of technical expertise, you are expected to demonstrate proficiency in areas such as microservices architecture, Docker, Kubernetes, ML Ops, Machine Learning workflows using tools like Spark, SQL, PySpark programming, Big Data solutions like Spark and Hive, Airflow, Python programming with frameworks like FastAPI, data engineering, unit testing, code quality assurance, and Git. Practical knowledge of cloud-based data stores, cloud solution architecture (especially GCP and Azure), GitLab CI/CD pipelines, monitoring, alerting systems, scalable architectures, and distributed processing frameworks is also appreciated. Soft skills such as collaborative teamwork, troubleshooting complex systems, and familiarity with GitLab for CI/CD and infrastructure automation tools are considered additional plus points. The company promises to exceed your expectations by offering a rewarding benefits package, personal flexibility, thoughtful perks like flexible working hours and birthday off, and an environment that fosters growth and innovation.,

Experience as a DevOps Engineer. Good knowledge of CI/CD tools like Jenkins Proficient with Python/Golang Good knowledge of AWS, Docker, and Kubernetes. Ml ops, Airflow and LLM Deployment. Infrastructure scaling.

One of the Healthcare AI Product Start up based out of Hyderabad is looking out for a AI Architect. If you are looking for a challenging environment and would like to be a part of building AI products, let us connect and discuss. Position: AI Architect Experience: 5+ yrs Qualification: B.Tech / B.E from Tier 1 Academic Institutions Job Type: Permanent & Hybrid Model Job Location: Hyderabad Position Overview We are seeking an experienced AI Architect to lead the design, development, and deployment of large-scale AI solutions. The ideal candidate will bridge the gap between business requirements and technical implementation, with deep expertise in generative AI and modern MLOps practices. Key Responsibilities: AI Solution Design & Implementation: • Architect end-to-end AI systems leveraging large language models and generative AI technologies • Design scalable, production-ready AI applications that meet business objectives and performance requirements • Evaluate and integrate LLM APIs from leading providers (OpenAI, Anthropic Claude, Google Gemini, etc.) • Establish best practices for prompt engineering, model selection, and AI system optimization Model Development & Fine-tuning: • Fine-tune open-source models (Llama, Mistral, etc.) for specific business use cases • Implement custom training pipelines and evaluation frameworks • Optimize model performance, latency, and cost for production environments • Stay current with latest model architectures and fine-tuning techniques Infrastructure & Deployment: • Deploy and manage AI models at enterprise scale using containerization (Docker) and orchestration (Kubernetes) • Build robust, scalable APIs using FastAPI and similar frameworks • Design and implement MLOps pipelines for model versioning, monitoring, and continuous deployment • Ensure high availability, security, and performance of AI systems in production Business & Technical Leadership: • Collaborate with stakeholders to understand business problems and translate them into technical requirements • Provide technical guidance and mentorship to development teams • Conduct feasibility assessments and technical due diligence for AI initiatives • Create technical documentation, architectural diagrams, and implementation roadmaps Required Qualifications: Experience • 5+ years of experience in machine learning engineering or data science • 1+ years of hands-on experience building, deploying, and managing generative AI models in production • Proven track record of delivering large-scale ML solutions Technical Skills: • Expert-level proficiency with LLM APIs (OpenAI, Claude, Gemini, etc.) • Hands-on experience fine-tuning transformer models (Llama, Mistral, etc.) • Strong proficiency in FastAPI, Docker, and Kubernetes • Experience with ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers) • Proficiency in Python and modern software development practices • Experience with cloud platforms (AWS, GCP, or Azure) and their AI/ML services Core Competencies: • Strong understanding of transformer architectures, attention mechanisms, and modern NLP techniques • Experience with MLOps tools and practices (model versioning, monitoring, CI/CD) • Ability to translate complex business requirements into technical solutions • Strong problem-solving skills and architectural thinking Preferred Qualifications: • Experience with vector databases and retrieval-augmented generation (RAG) systems • Knowledge of distributed training and model parallelization techniques • Experience with model quantization and optimization for edge deployment • Familiarity with AI safety, alignment, and responsible AI practices • Experience in specific domains (finance, healthcare, legal, etc.) • Advanced degree in Computer Science, AI/ML, or related field Please Note: We are looking out for candidates with shorter notice period.

You have the opportunity to join RiDiK Consulting Private Limited as a Senior Software Engineer specializing in ETL Testing with Python. The position is based in Pune and requires a notice period of 15 days or immediate availability. With over 7 years of experience in automation testing, particularly in a product organization, you will be responsible for the technical design, development, and deployment of automation frameworks for large core products and functional components using Python. Your role will involve developing automation frameworks for web, data pipeline, and API based applications. You will also lead technology stack evaluation and proof of concepts for automation processes. Collaboration is key in this role as you will work closely with application development, architecture, and infrastructure teams to drive automation, performance evaluation, and application analysis initiatives. Your expertise in Test Automation frameworks such as Junit, Selenium, DBUnit, and TestNG will be essential, along with a strong knowledge of SQL, ETL, and BI Report Testing. Your responsibilities will include extensive experience in ETL/Data warehouse backend testing, BI Intelligence report testing, API testing, and prior exposure to ML Ops systems. Any background in testing ML/AI based software and data output will be beneficial. Proficiency in test management tools like HP Quality Center, JIRA, and experience with SDLC & Agile Methodology will be required. Additionally, you should have excellent knowledge of Database Systems such as Vertica, Oracle, Teradata, and experience in Business Intelligence testing using tools like Tableau. Your strong comprehension, analytical, and problem-solving skills will be valuable assets in this role. Knowledge of AWS, testing data science projects, and working with enterprise application architecture and technologies are important qualifications for this position. Overall, your role as a Senior Software Engineer at RiDiK Consulting Private Limited will involve developing automation frameworks, managing end-to-end automated test cases, reporting, and bug tracking, while ensuring a deep understanding of enterprise application architecture and technologies.,

One of the Healthcare AI Product Start ups based out of Hyderabad is looking out for a AI Architect. If you are looking for a challenging environment and would like to be a part of building AI products in a start up environment, let us connect and discuss. Title: AI Engineer Experience: 3 to 5 yrs Qualification: B.Tech / M.Tech Job Location: Hyderabad Job Type & Model: Permanent & Hybrid Position Overview: We are looking for a skilled AI Engineer to develop, implement, and optimize AI solutions using cutting-edge generative AI technologies. This role focuses on hands-on development of AI applications, model integration, and production deployment while working closely with our AI architecture team. Key Responsibilities: AI Application Development: Build and maintain AI-powered applications using LLM APIs (OpenAI, Claude, Gemini, etc.) Implement prompt engineering strategies and optimize model interactions for performance and cost Develop custom AI workflows including retrieval-augmented generation (RAG) systems Create robust error handling, fallback mechanisms, and response validation systems Model Implementation & Fine-tuning: Fine-tune open-source models (Llama, Mistral, etc.) for specific use cases and domains Implement training pipelines using modern frameworks (PyTorch, Hugging Face Transformers) Conduct model evaluation, A/B testing, and performance optimization Manage model versioning and experiment tracking Production Deployment & Operations: Deploy AI models and applications using FastAPI, Docker, and Kubernetes Build scalable microservices architecture for AI applications Implement monitoring, logging, and alerting for production AI systems Optimize inference performance, latency, and resource utilization Integration & Data Engineering: Integrate AI capabilities into existing systems and workflows Build data pipelines for model training and inference Work with vector databases and embedding systems Implement caching strategies and data preprocessing pipelines Experience: 3+ years of experience in machine learning or software engineering 1+ years of hands-on experience with generative AI and LLM integration Demonstrated experience deploying ML models in production environments Technical Skills: Proficiency with LLM APIs and SDKs (OpenAI, Anthropic, Google, etc.) Experience fine-tuning transformer models using Hugging Face, PyTorch, or similar Strong proficiency in Python and modern software development practices Hands-on experience with FastAPI, Docker, and containerization Experience with Kubernetes for container orchestration Knowledge of RESTful API design and microservices architecture Core Competencies: Understanding of transformer architectures, embeddings, and attention mechanisms Experience with prompt engineering and model optimization techniques Familiarity with MLOps practices and tools (model versioning, monitoring, CI/CD) Strong debugging and troubleshooting skills Ability to work with large-scale data and distributed systems

Exp: 5+ yrs in Machine Learning Engineering big data technologies ( Spark, Hadoop, Kafka) A/B testing and experimental design for ML models Knowledge of data governance,privacy & security best practices in ML share CV-garimaimaginators@gmail.com Required Candidate profile Exceptional Programming Skills: Expert-level proficiency in Python, including experience with writing production-grade End-to-End ML Application Development Software Design & Architecture

We are hiring a AIML Technical Lead for the Noida location. Any graduate can apply. Job description Technical Skillset : Must Have Skills - Generative AI - GPT3, ML Ops and Python Proficient in Python, with experience in machine learning, deep learning, and NLP processing. Experience in developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs. Proficient in Langchain, LLM Prompt Engineering : The engineer prompts and optimizes few-shot techniques to enhance LLM's performance on specific tasks, e.g. personalized recommendations. Model Evaluation & Optimization : Evaluate LLM's zero-shot and few-shot capabilities, fine-tuning hyperparameters, ensuring task generalization, and exploring model interpretability for robust web app integration. Response Quality : Collaborate with ML and Integration engineers to leverage LLM's pre-trained potential, delivering contextually appropriate responses in a user-friendly web app. It is essential to have a solid understanding of data structures, algorithms, and principles of software engineering. Experience with vector databases RDBMS, MongoDB and NoSQL databases. Proficiency in working with embeddings. Strong distributed systems skills and system architecture skills Experienced in building and running a large platform at scale. Hands-on experience with Python, Hugging Face, TensorFlow, Keras, PyTorch, Spark, or similar statistical tools. Experience as data modeling ML/NLP scientist. including, but not limited to, Performance tuning, fine-tuning, RLHF, and performance optimization. Validated background with ML toolkits, such as PyTorch, TensorFlow, Keras, Langchain, Llamadindex, SparkML, or Databricks. Proficient with the integration of data from multiple data sources Experience with NoSQL databases, such as HBase, ElasticSearch, and MongoDB API Design. API/Data mapping to schema. Experienced in and strong knowledge of using AI/ML and more particularly LLMs eager to apply this rapidly changing technology. Good Knowledge of Kubernetes, and RESTful design. Prior experience in developing public cloud services or open-source ML software is an advantage Role and responsibilities - Collaborating with cross-functional teams to define AI project requirements and objectives ensuring alignment with overall business goals Conducting research to stay up to date with the latest advancements in generative AI machine learning and deep learning techniques and identify opportunities to integrate them into our products and services. Optimizing existing generative AI models for improved performance scalability and efficiency. Active participation in developer communities, open-source contributions, or personal GenAI projects Work closely with the GenAI development team to integrate AI models and applications with the existing/new tool, quality, and performance. Act as an authority, guiding junior engineers and collaborating teams, fostering a culture of development excellence, collaboration, and continuous learning. Evaluating and selecting appropriate AI tools and machine learning models for tasks, as well as building and training working versions of those models using Python and other open-source technologies Working with leadership and stakeholders to identify AI opportunities and promote strategy. Serve as a technical lead, overseeing and supervising projects and engineers on the team. Play a leading hands-on role in the design and implementation of our ML infrastructure and GenAI platform software technologies. Drive our technology vision and roadmap. Establish software development best practices, and lead by example in applying them Experience contributing to the architecture and design of large scale distributed systems and/or ML systems and tools Hands-on experience leveraging large sets of structured and unstructured data to develop data-driven tactical and strategic analytics and insights using ML, NLP, computer vision solutions Strong sense of software design and usability of ML systems Experience applying software engineering methodologies and best practices including coding standards, code reviews, build processes, testing, and security. Proven experience as a Engineering Lead, hands on Software Engineering Manager, or similar role Develop natural language processing (NLP) solutions using GenAI, LLMs and custom transformer architectures. Adopt and customize LLM agent-based orchestration tools (LlamaIndex, Langchain, Semantic Kernel) for enterprise applications and use cases Implement information search and retrieval at scale, using a range of solutions ranging from keyword search to semantic search using embeddings. Developing and/or tune Large Language Models (LLM) and Generative AI (GAI) Analyze, design, develop, support and maintain Big Data environment and code base, support traditional data pipelines and processes. Education Computer science, Data Engineering, or a related field graduates. Sal upto 25 LPA Regards SPARK CONSULTANCY

We are hiring a AIML Technical Lead for the Noida location. Any graduate can apply. Job description Technical Skillset : Must Have Skills - Generative AI - GPT3, ML Ops and Python Proficient in Python, with experience in machine learning, deep learning, and NLP processing. Experience in developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs. Proficient in Langchain, LLM Prompt Engineering : The engineer prompts and optimizes few-shot techniques to enhance LLM's performance on specific tasks, e.g. personalized recommendations. Model Evaluation & Optimization : Evaluate LLM's zero-shot and few-shot capabilities, fine-tuning hyperparameters, ensuring task generalization, and exploring model interpretability for robust web app integration. Response Quality : Collaborate with ML and Integration engineers to leverage LLM's pre-trained potential, delivering contextually appropriate responses in a user-friendly web app. It is essential to have a solid understanding of data structures, algorithms, and principles of software engineering. Experience with vector databases RDBMS, MongoDB and NoSQL databases. Proficiency in working with embeddings. Strong distributed systems skills and system architecture skills Experienced in building and running a large platform at scale. Hands-on experience with Python, Hugging Face, TensorFlow, Keras, PyTorch, Spark, or similar statistical tools. Experience as data modeling ML/NLP scientist. including, but not limited to, Performance tuning, fine-tuning, RLHF, and performance optimization. Validated background with ML toolkits, such as PyTorch, TensorFlow, Keras, Langchain, Llamadindex, SparkML, or Databricks. Proficient with the integration of data from multiple data sources Experience with NoSQL databases, such as HBase, ElasticSearch, and MongoDB API Design. API/Data mapping to schema. Experienced in and strong knowledge of using AI/ML and more particularly LLMs eager to apply this rapidly changing technology. Good Knowledge of Kubernetes, and RESTful design. Prior experience in developing public cloud services or open-source ML software is an advantage Role and responsibilities - Collaborating with cross-functional teams to define AI project requirements and objectives ensuring alignment with overall business goals Conducting research to stay up to date with the latest advancements in generative AI machine learning and deep learning techniques and identify opportunities to integrate them into our products and services. Optimizing existing generative AI models for improved performance scalability and efficiency. Active participation in developer communities, open-source contributions, or personal GenAI projects Work closely with the GenAI development team to integrate AI models and applications with the existing/new tool, quality, and performance. Act as an authority, guiding junior engineers and collaborating teams, fostering a culture of development excellence, collaboration, and continuous learning. Evaluating and selecting appropriate AI tools and machine learning models for tasks, as well as building and training working versions of those models using Python and other open-source technologies Working with leadership and stakeholders to identify AI opportunities and promote strategy. Serve as a technical lead, overseeing and supervising projects and engineers on the team. Play a leading hands-on role in the design and implementation of our ML infrastructure and GenAI platform software technologies. Drive our technology vision and roadmap. Establish software development best practices, and lead by example in applying them Experience contributing to the architecture and design of large scale distributed systems and/or ML systems and tools Hands-on experience leveraging large sets of structured and unstructured data to develop data-driven tactical and strategic analytics and insights using ML, NLP, computer vision solutions Strong sense of software design and usability of ML systems Experience applying software engineering methodologies and best practices including coding standards, code reviews, build processes, testing, and security. Proven experience as a Engineering Lead, hands on Software Engineering Manager, or similar role Develop natural language processing (NLP) solutions using GenAI, LLMs and custom transformer architectures. Adopt and customize LLM agent-based orchestration tools (LlamaIndex, Langchain, Semantic Kernel) for enterprise applications and use cases Implement information search and retrieval at scale, using a range of solutions ranging from keyword search to semantic search using embeddings. Developing and/or tune Large Language Models (LLM) and Generative AI (GAI) Analyze, design, develop, support and maintain Big Data environment and code base, support traditional data pipelines and processes. Education Computer science, Data Engineering, or a related field graduates. Sal upto 25 LPA Regards SPARK CONSULTANCY

We are hiring a AIML Technical Lead for the Noida location. Any graduate can apply. Job description Technical Skillset : Must Have Skills - Generative AI - GPT3, ML Ops and Python Proficient in Python, with experience in machine learning, deep learning, and NLP processing. Experience in developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs. Proficient in Langchain, LLM Prompt Engineering : The engineer prompts and optimizes few-shot techniques to enhance LLM's performance on specific tasks, e.g. personalized recommendations. Model Evaluation & Optimization : Evaluate LLM's zero-shot and few-shot capabilities, fine-tuning hyperparameters, ensuring task generalization, and exploring model interpretability for robust web app integration. Response Quality : Collaborate with ML and Integration engineers to leverage LLM's pre-trained potential, delivering contextually appropriate responses in a user-friendly web app. It is essential to have a solid understanding of data structures, algorithms, and principles of software engineering. Experience with vector databases RDBMS, MongoDB and NoSQL databases. Proficiency in working with embeddings. Strong distributed systems skills and system architecture skills Experienced in building and running a large platform at scale. Hands-on experience with Python, Hugging Face, TensorFlow, Keras, PyTorch, Spark, or similar statistical tools. Experience as data modeling ML/NLP scientist. including, but not limited to, Performance tuning, fine-tuning, RLHF, and performance optimization. Validated background with ML toolkits, such as PyTorch, TensorFlow, Keras, Langchain, Llamadindex, SparkML, or Databricks. Proficient with the integration of data from multiple data sources Experience with NoSQL databases, such as HBase, ElasticSearch, and MongoDB API Design. API/Data mapping to schema. Experienced in and strong knowledge of using AI/ML and more particularly LLMs eager to apply this rapidly changing technology. Good Knowledge of Kubernetes, and RESTful design. Prior experience in developing public cloud services or open-source ML software is an advantage Role and responsibilities - Collaborating with cross-functional teams to define AI project requirements and objectives ensuring alignment with overall business goals Conducting research to stay up to date with the latest advancements in generative AI machine learning and deep learning techniques and identify opportunities to integrate them into our products and services. Optimizing existing generative AI models for improved performance scalability and efficiency. Active participation in developer communities, open-source contributions, or personal GenAI projects Work closely with the GenAI development team to integrate AI models and applications with the existing/new tool, quality, and performance. Act as an authority, guiding junior engineers and collaborating teams, fostering a culture of development excellence, collaboration, and continuous learning. Evaluating and selecting appropriate AI tools and machine learning models for tasks, as well as building and training working versions of those models using Python and other open-source technologies Working with leadership and stakeholders to identify AI opportunities and promote strategy. Serve as a technical lead, overseeing and supervising projects and engineers on the team. Play a leading hands-on role in the design and implementation of our ML infrastructure and GenAI platform software technologies. Drive our technology vision and roadmap. Establish software development best practices, and lead by example in applying them Experience contributing to the architecture and design of large scale distributed systems and/or ML systems and tools Hands-on experience leveraging large sets of structured and unstructured data to develop data-driven tactical and strategic analytics and insights using ML, NLP, computer vision solutions Strong sense of software design and usability of ML systems Experience applying software engineering methodologies and best practices including coding standards, code reviews, build processes, testing, and security. Proven experience as a Engineering Lead, hands on Software Engineering Manager, or similar role Develop natural language processing (NLP) solutions using GenAI, LLMs and custom transformer architectures. Adopt and customize LLM agent-based orchestration tools (LlamaIndex, Langchain, Semantic Kernel) for enterprise applications and use cases Implement information search and retrieval at scale, using a range of solutions ranging from keyword search to semantic search using embeddings. Developing and/or tune Large Language Models (LLM) and Generative AI (GAI) Analyze, design, develop, support and maintain Big Data environment and code base, support traditional data pipelines and processes. Education Computer science, Data Engineering, or a related field graduates. Sal upto 25 LPA Regards SPARK CONSULTANCY

We are hiring a AIML Technical Lead for the Noida location. Any graduate can apply. Job description Technical Skillset : Must Have Skills - Generative AI - GPT3, ML Ops and Python Proficient in Python, with experience in machine learning, deep learning, and NLP processing. Experience in developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs. Proficient in Langchain, LLM Prompt Engineering : The engineer prompts and optimizes few-shot techniques to enhance LLM's performance on specific tasks, e.g. personalized recommendations. Model Evaluation & Optimization : Evaluate LLM's zero-shot and few-shot capabilities, fine-tuning hyperparameters, ensuring task generalization, and exploring model interpretability for robust web app integration. Response Quality : Collaborate with ML and Integration engineers to leverage LLM's pre-trained potential, delivering contextually appropriate responses in a user-friendly web app. It is essential to have a solid understanding of data structures, algorithms, and principles of software engineering. Experience with vector databases RDBMS, MongoDB and NoSQL databases. Proficiency in working with embeddings. Strong distributed systems skills and system architecture skills Experienced in building and running a large platform at scale. Hands-on experience with Python, Hugging Face, TensorFlow, Keras, PyTorch, Spark, or similar statistical tools. Experience as data modeling ML/NLP scientist. including, but not limited to, Performance tuning, fine-tuning, RLHF, and performance optimization. Validated background with ML toolkits, such as PyTorch, TensorFlow, Keras, Langchain, Llamadindex, SparkML, or Databricks. Proficient with the integration of data from multiple data sources Experience with NoSQL databases, such as HBase, ElasticSearch, and MongoDB API Design. API/Data mapping to schema. Experienced in and strong knowledge of using AI/ML and more particularly LLMs eager to apply this rapidly changing technology. Good Knowledge of Kubernetes, and RESTful design. Prior experience in developing public cloud services or open-source ML software is an advantage Role and responsibilities - Collaborating with cross-functional teams to define AI project requirements and objectives ensuring alignment with overall business goals Conducting research to stay up to date with the latest advancements in generative AI machine learning and deep learning techniques and identify opportunities to integrate them into our products and services. Optimizing existing generative AI models for improved performance scalability and efficiency. Active participation in developer communities, open-source contributions, or personal GenAI projects Work closely with the GenAI development team to integrate AI models and applications with the existing/new tool, quality, and performance. Act as an authority, guiding junior engineers and collaborating teams, fostering a culture of development excellence, collaboration, and continuous learning. Evaluating and selecting appropriate AI tools and machine learning models for tasks, as well as building and training working versions of those models using Python and other open-source technologies Working with leadership and stakeholders to identify AI opportunities and promote strategy. Serve as a technical lead, overseeing and supervising projects and engineers on the team. Play a leading hands-on role in the design and implementation of our ML infrastructure and GenAI platform software technologies. Drive our technology vision and roadmap. Establish software development best practices, and lead by example in applying them Experience contributing to the architecture and design of large scale distributed systems and/or ML systems and tools Hands-on experience leveraging large sets of structured and unstructured data to develop data-driven tactical and strategic analytics and insights using ML, NLP, computer vision solutions Strong sense of software design and usability of ML systems Experience applying software engineering methodologies and best practices including coding standards, code reviews, build processes, testing, and security. Proven experience as a Engineering Lead, hands on Software Engineering Manager, or similar role Develop natural language processing (NLP) solutions using GenAI, LLMs and custom transformer architectures. Adopt and customize LLM agent-based orchestration tools (LlamaIndex, Langchain, Semantic Kernel) for enterprise applications and use cases Implement information search and retrieval at scale, using a range of solutions ranging from keyword search to semantic search using embeddings. Developing and/or tune Large Language Models (LLM) and Generative AI (GAI) Analyze, design, develop, support and maintain Big Data environment and code base, support traditional data pipelines and processes. Education Computer science, Data Engineering, or a related field graduates. Sal upto 25 LPA Regards SPARK CONSULTANCY

We are hiring a AIML Technical Lead for the Noida location. Any graduate can apply. Job description Technical Skillset : Must Have Skills - Generative AI - GPT3, ML Ops and Python Proficient in Python, with experience in machine learning, deep learning, and NLP processing. Experience in developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs. Proficient in Langchain, LLM Prompt Engineering : The engineer prompts and optimizes few-shot techniques to enhance LLM's performance on specific tasks, e.g. personalized recommendations. Model Evaluation & Optimization : Evaluate LLM's zero-shot and few-shot capabilities, fine-tuning hyperparameters, ensuring task generalization, and exploring model interpretability for robust web app integration. Response Quality : Collaborate with ML and Integration engineers to leverage LLM's pre-trained potential, delivering contextually appropriate responses in a user-friendly web app. It is essential to have a solid understanding of data structures, algorithms, and principles of software engineering. Experience with vector databases RDBMS, MongoDB and NoSQL databases. Proficiency in working with embeddings. Strong distributed systems skills and system architecture skills Experienced in building and running a large platform at scale. Hands-on experience with Python, Hugging Face, TensorFlow, Keras, PyTorch, Spark, or similar statistical tools. Experience as data modeling ML/NLP scientist. including, but not limited to, Performance tuning, fine-tuning, RLHF, and performance optimization. Validated background with ML toolkits, such as PyTorch, TensorFlow, Keras, Langchain, Llamadindex, SparkML, or Databricks. Proficient with the integration of data from multiple data sources Experience with NoSQL databases, such as HBase, ElasticSearch, and MongoDB API Design. API/Data mapping to schema. Experienced in and strong knowledge of using AI/ML and more particularly LLMs eager to apply this rapidly changing technology. Good Knowledge of Kubernetes, and RESTful design. Prior experience in developing public cloud services or open-source ML software is an advantage Role and responsibilities - Collaborating with cross-functional teams to define AI project requirements and objectives ensuring alignment with overall business goals Conducting research to stay up to date with the latest advancements in generative AI machine learning and deep learning techniques and identify opportunities to integrate them into our products and services. Optimizing existing generative AI models for improved performance scalability and efficiency. Active participation in developer communities, open-source contributions, or personal GenAI projects Work closely with the GenAI development team to integrate AI models and applications with the existing/new tool, quality, and performance. Act as an authority, guiding junior engineers and collaborating teams, fostering a culture of development excellence, collaboration, and continuous learning. Evaluating and selecting appropriate AI tools and machine learning models for tasks, as well as building and training working versions of those models using Python and other open-source technologies Working with leadership and stakeholders to identify AI opportunities and promote strategy. Serve as a technical lead, overseeing and supervising projects and engineers on the team. Play a leading hands-on role in the design and implementation of our ML infrastructure and GenAI platform software technologies. Drive our technology vision and roadmap. Establish software development best practices, and lead by example in applying them Experience contributing to the architecture and design of large scale distributed systems and/or ML systems and tools Hands-on experience leveraging large sets of structured and unstructured data to develop data-driven tactical and strategic analytics and insights using ML, NLP, computer vision solutions Strong sense of software design and usability of ML systems Experience applying software engineering methodologies and best practices including coding standards, code reviews, build processes, testing, and security. Proven experience as a Engineering Lead, hands on Software Engineering Manager, or similar role Develop natural language processing (NLP) solutions using GenAI, LLMs and custom transformer architectures. Adopt and customize LLM agent-based orchestration tools (LlamaIndex, Langchain, Semantic Kernel) for enterprise applications and use cases Implement information search and retrieval at scale, using a range of solutions ranging from keyword search to semantic search using embeddings. Developing and/or tune Large Language Models (LLM) and Generative AI (GAI) Analyze, design, develop, support and maintain Big Data environment and code base, support traditional data pipelines and processes. Education Computer science, Data Engineering, or a related field graduates. Sal upto 25 LPA Regards SPARK CONSULTANCY

We are looking for a skilled and innovative Machine Learning Engineer with expertise in Large Language Models (LLMs) to join our team. The ideal candidate should have hands-on experience in developing, fine-tuning, and deploying LLMs, along with a deep understanding of the machine learning lifecycle. Your responsibilities will include developing and optimizing LLMs such as OpenAI's GPT, Anthropic's Claude, Google's Gemini, or AWS Bedrock. You will customize pre-trained models for specific use cases to ensure high performance and scalability. Additionally, you will be responsible for designing and maintaining end-to-end ML pipelines from data preprocessing to model deployment, optimizing training workflows for efficiency and accuracy. Collaboration with cross-functional teams, integration of ML solutions into production environments, experimentation with new approaches to improve model performance, and staying updated with advancements in LLMs and generative AI technologies will also be part of your role. You will collaborate with data scientists, engineers, and product managers to align ML solutions with business goals and provide mentorship to junior team members. The qualifications we are looking for include at least 5 years of professional experience in machine learning or AI development, proven expertise with LLMs and generative AI technologies, proficiency in Python (required) and/or Java (bonus), hands-on experience with APIs and tools like OpenAI, Anthropic's Claude, Google Gemini, or AWS Bedrock, familiarity with ML frameworks such as TensorFlow, PyTorch, or Hugging Face, and a strong understanding of data structures, algorithms, and distributed systems. Cloud expertise in AWS, GCP, or Azure, including services relevant to ML workloads such as AWS SageMaker and Bedrock, proficiency in handling large-scale datasets and implementing data pipelines, experience with ETL tools and platforms for efficient data preprocessing, strong analytical and problem-solving skills, and the ability to debug and resolve issues quickly are also required. Preferred qualifications include experience with multi-modal models, generative AI for images, text, or other modalities, understanding of ML Ops principles and tools like MLflow and Kubeflow, familiarity with reinforcement learning and distributed training techniques and tools like Horovod or Ray, and an advanced degree (Master's or Ph.D) in Computer Science, Machine Learning, or a related field.,

DESCRIPTION As a Research Analyst, you'll collaborate with experts to develop cutting-edge ML and Gen AI/LLM solutions for business needs. You'll drive product pilots, demonstrating innovative thinking and customer focus. You'll coordinate between science and software teams, optimizing solutions. The role requires thriving in ambiguous, fast-paced environments and working independently with ML models. You are expected to be an Expert in classical ML, generative AI, prompt engineering, and deployment optimization. Capable of building scalable and production-ready AI systems. Provide mentorship and guidance to junior members in the team. Engage in cross-functional collaboration and drive measurable business impact Key job responsibilities . Collaborate with seasoned Applied Scientists and propose best in class ML solutions for business requirements . Dive deep to drive product pilots, demonstrate think big and customer obsession LPs to steer the product roadmap . Build scalable solutions in partnership with Applied Scientists by developing technical intuition to write high quality code and develop state of the art ML models utilizing most recent research breakthroughs in academia and industry . Coordinate design efforts between Sciences and Software teams to deliver optimized solutions . Ability to thrive in an ambiguous, uncertain and fast moving ML usecase developments. . . Lead the design and deployment of hybrid ML/LLM systems (e.g., RAG pipelines, fine-tuned models) . Conduct thorough ML experimentation and make ML model and architecture design choices. . Conduct hyperparameter tuning, prompt optimization, and performance monitoring at scale . Work on ML Ops to implement reproducible pipelines and experiment tracking . Translate ambiguous business problems into AI/ML solutions . Mentor Junior Research Analyst (RAs) and contribute to RA hiring About the team Retail Business Services Technology (RBS Tech) team develops the systems and science to accelerate Amazon's flywheel. The team drives three core themes: 1) Find and Fix all customer and selling partner experience (CX and SPX) defects using technology, 2) Generate comprehensive insights for brand growth opportunities, and 3) Completely automate Stores tasks. Our vision for MLOE is to achieve ML operational excellence across Amazon through continuous innovation, scalable infrastructure, and a data-driven approach to optimize value, efficiency, and reliability. We focus on key areas for enhancing machine learning operations: a) Model Evaluation: Expanding LLM-based audit platform to support multilingual and multimodal auditing. Developing an LLM-powered testing framework for conversational systems to automate the validation of conversational flows, ensuring scalable, accurate, and efficient end-to-end testing. b) Guardrails: Building common guardrail APIs that teams can integrate to detect and prevent egregious errors, knowledge grounding issues, PII breaches, and biases. c) Deployment Framework support LLM deployments and seamlessly integrate it with our release management processes. BASIC QUALIFICATIONS - . Bachelor's degree in Quantitative or STEM disciplines (Science, Technology, Engineering, Mathematics) - . 3+ years of relevant work experience in solving real world business problems using AI/ML or applying GenAI and LLMs through prompt engineering techniques. - . Strong hands-on programming skills in Python, SQL. - . Strong analytical thinking - . Ability to creatively solve business problems, innovating new approaches where required and articulating ideas to a wide range of audiences using strong data, written and verbal communication skills - . Ability to collaborate effectively across multiple tech and business teams. PREFERRED QUALIFICATIONS - . Master's degree with specialization in ML, NLP or Computer Vision preferred - . Diverse experience will be favored eg. a mix of experience across different roles - In-depth understanding of machine learning concepts including developing models and tuning the hyper-parameters, as well as deploying models and building ML service - Technical expertise, experience in AI/ML and GenAI Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

We are searching for a Lead Data Scientist to become a valuable member of our collaborative team. Your main responsibility will involve creating and implementing AI solutions across a variety of applications, ranging from statistical analysis to natural language processing. If you have a strong passion for utilizing data to develop impactful solutions, we highly encourage you to submit your application. Your primary responsibilities will include developing and deploying AI solutions such as classification, clustering, and anomaly detection. You will be tasked with conducting statistical data analysis, applying machine learning techniques, and overseeing the entire project lifecycle from data preparation to model evaluation. Your expertise in Python programming and SQL will be essential for data manipulation and analysis, as well as engaging in ML Ops and model development workflows. Furthermore, you will collaborate with teams utilizing software development methodologies and version control, while documenting processes and utilizing project tracking tools like Jira. To qualify for this role, you should possess at least 9 years of experience in software engineering, with a specialization in Data Science, along with a minimum of 1 year of relevant leadership experience. Proficiency in statistical data analysis, machine learning, and NLP is required, with a deep understanding of their practical applications and limitations. Additionally, experience in developing AI solutions, including classification, clustering, anomaly detection, and NLP is crucial. Your expertise in complete project delivery, Python programming, SQL, ML Ops, model development workflows, and feature engineering techniques will be vital for success in this role. You must also demonstrate competence in data manipulation, developing business-accessible models, and have experience in Azure AI Search. Familiarity with software development methodologies, code versioning (e.g., GitLab), and project tracking tools (e.g., Jira) is necessary. Enthusiasm for learning new technologies, problem-solving, and delivering production-ready solutions is highly valued. Fluency in UNIX command line and familiarity with Agile development practices are desired. Excellent communication skills in English, with a minimum proficiency level of B2+, are essential for effective collaboration. Nice to have qualifications include knowledge of Cloud Computing, experience with Big Data tools, familiarity with visualization tools, and proficiency in containerization tools.,

Job Description ML Ops Engineer (2–3 Years Experience) Position Overview We are looking for a passionate and skilled ML Ops Engineer with 2–3 years of experience to join our AI initiatives and services team. The ideal candidate will not only be strong in operationalizing machine learning workflows but also have hands-on exposure or working knowledge in Large Language Models (LLMs), Computer Vision, Speech-to-Text, and Image Recognition to solve real-world problems. This role requires strong adaptability to multiple technologies, excellent communication skills, and a creative problem-solving mindset to bridge the gap between AI research and scalable business solutions. Key Responsibilities Design, build, and maintain end-to-end ML Ops pipelines for deploying and scaling ML/AI models. Automate workflows for model training, deployment, monitoring, and retraining. Ensure scalability, reliability, and performance of ML systems in production. Work with ML Engineers and Data Scientists to bring models from experimentation to production . Manage model versioning, governance, monitoring, and logging . Implement CI/CD for ML workloads with Docker/Kubernetes and cloud platforms (Azure, AWS, or GCP). Support integration of models into client-facing applications and services. Apply ML Ops practices to LLMs, Vision, Speech-to-Text, and Image Recognition use cases . Stay up to date with emerging AI tools and frameworks (LangChain, Hugging Face, OpenAI APIs, etc.) and apply them to real-world problem solving. Required Skills & Qualifications 2–3 years of professional experience in ML Ops / Data Engineering / AI Engineering . Strong programming skills in Python with experience in ML frameworks (TensorFlow, PyTorch, Scikit-learn). Hands-on experience with ML Ops tools (MLflow, Kubeflow, Airflow, DVC, or similar). Solid knowledge of CI/CD pipelines , Docker, Kubernetes, and cloud services (Azure ML, AWS Sagemaker, or GCP Vertex AI). Familiarity with LLMs, Vision, Speech-to-Text, and Image Recognition techniques — practical experience or strong conceptual knowledge. Understanding of prompt engineering, model fine-tuning, or transfer learning is a plus. Excellent problem-solving skills, creativity, and the ability to adapt quickly to new technologies. Strong communication and collaboration skills to work effectively with cross-functional teams and clients. Preferred Skills Exposure to LangChain, Hugging Face Transformers, or RAG-based systems . Experience working with APIs and microservices to serve AI models. Knowledge of monitoring tools for deployed AI models (Prometheus, Grafana, EvidentlyAI). Familiarity with handling unstructured data (text, audio, images, video). Education Bachelor’s or master’s degree in computer science , Data Science, AI/ML, or related field . What We Look For A strong ownership mindset with the ability to deliver end-to-end solutions. Passion for solving real-world business challenges using AI. Professionals who can communicate complex concepts clearly to both technical and non-technical audiences. A creative thinker who stays ahead of trends in AI/ML and ML Ops practices.

Job Description: AI/ML Model Development & Deployment Focused on marketing and operations use cases Deep Learning – CNNs, RNNs, Transformers, Attention Mechanisms Generative AI – Experience with OpenAI (GPT, DALL•E, Whisper) and Anthropic (Claude) Agentic AI Platforms – AutoGen, CrewAI, AWS Bedrock Multimodal AI – Building agents using text, voice, and other inputs for automation Python Programming – Proficient with NumPy, Pandas, Matplotlib, TensorFlow, PyTorch Traditional ML Techniques – Supervised/Unsupervised Learning, PCA, Feature Engineering, Model Evaluation, Hyperparameter Tuning Data Analytics – Predictive analysis, clustering, A/B testing, KPI monitoring MLOps & CI/CD – Model versioning, deployment pipelines, monitoring Cloud Services – AWS (S3, Lambda, EC2, SageMaker, Bedrock), Serverless architectures Development Tools – Proficient in using Cursor for design, development, and code reviews Communication & Collaboration – Strong communication skills and client engagement experience Power BI/Tableu is good to have Domain Expertise – Marketing-focused AI solutions (big plus)