1576 Sagemaker Jobs - Page 39

As part of our full-stack product engineering team, you will build multi-tenant cloud-based software products/platforms and internal assets that will leverage cutting edge based on the Amazon AWS cloud platform. Pair program, write unit tests, lead code reviews, and collaborate with QA analysts to ensure you develop the highest quality multi-tenant software that can be productized. Work with junior developers to implement large features that are on the cutting edge of Big Data Be a technical leader to your team, and help them improve their technical skills Stand up for engineering practices that ensure quality products: automated testing, unit testing, agile development, continuous integration, code reviews, and technical design Work with product managers and architects to design product architecture and to work on POCs Take immediate responsibility for project deliverables Understand client business issues and design features that meet client needs Undergo on-the-job and formal trainings and certifications, and will constantly advance your knowledge and problem solving skills What youll bring: 1-3 years of experience in developing software, ideally building SaaS products and services Bachelors Degree in CS, IT, or related discipline Strong analytic, problem solving, and programming ability Good hands on to work with AWS services (EC2, EMR, S3, Serverless stack, RDS, Sagemaker, IAM, EKS etc) Experience in coding in an object-oriented language such as Python, Java, C# etc. Hands on experience on Apache Spark, EMR, Hadoop, HDFS, or other big data technologies Experience with development on the AWS (Amazon Web Services) platform is preferable Experience in Linux shell or PowerShell scripting is preferable Experience in HTML5, JavaScript, and JavaScript libraries is preferable Good to have Pharma domain understanding Initiative and drive to contribute Excellent organizational and task management skills Strong communication skills Ability to work in global cross-office teams ZS is a global firm; fluency in English is required

ZS s Beyond Healthcare Analytics (BHCA) Team is shaping one of the key growth vector area for ZS, Beyond Healthcare engagement, comprising of clients from industries like Quick service restaurants, Technology, Food & Beverage, Hospitality, Travel, Insurance, Consumer Products Goods & other such industries across North America, Europe & South East Asia region. BHCA India team currently has presence across New Delhi, Pune and Bengaluru offices and is continuously expanding further at a great pace. BHCA India team works with colleagues across clients and geographies to create and deliver real world pragmatic solutions leveraging AI SaaS products & platforms, Generative AI applications, and other Advanced analytics solutions at scale. What You'll Do: Build, Refine and Use ML Engineering platforms and components. Scaling machine learning algorithms to work on massive data sets and strict SLAs. Build and orchestrate model pipelines including feature engineering, inferencing and continuous model training. Implement ML Ops including model KPI measurements, tracking, model drift & model feedback loop. Collaborate with client facing teams to understand business context at a high level and contribute in technical requirement gathering. Implement basic features aligning with technical requirements. Write production-ready code that is easily testable, understood by other developers and accounts for edge cases and errors. Ensure highest quality of deliverables by following architecture/design guidelines, coding best practices, periodic design/code reviews. Write unit tests as well as higher level tests to handle expected edge cases and errors gracefully, as well as happy paths. Uses bug tracking, code review, version control and other tools to organize and deliver work. Participate in scrum calls and agile ceremonies, and effectively communicate work progress, issues and dependencies. Consistently contribute in researching & evaluating latest architecture patterns/technologies through rapid learning, conducting proof-of-concepts and creating prototype solutions. What You'll Bring A master's or bachelor s degree in Computer Science or related field from a top university. 4+ years hands-on experience in ML development. Good understanding of the fundamentals of machine learning Strong programming expertise in Python, PySpark/Scala. Expertise in crafting ML Models for high performance and scalability. Experience in implementing feature engineering, inferencing pipelines, and real time model predictions. Experience in ML Ops to measure and track model performance, experience working with MLFlow Experience with Spark or other distributed computing frameworks. Experience in ML platforms like Sage maker, Kubeflow. Experience with pipeline orchestration tools such Airflow. Experience in deploying models to cloud services like AWS, Azure, GCP, Azure ML. Expertise in SQL, SQL DB's. Knowledgeable of core CS concepts such as common data structures and algorithms. Collaborate well with teams with different backgrounds / expertise / functions

Job Title: Senior Data Scientist (Advanced Modeling & Machine Learning) Location: Remote Job Type: Full-time About the role We are seeking a highly motivated and experienced Senior Data Scientist with a strong background in statistical modeling, machine learning, and natural language processing (NLP). This individual will work on advanced attribution models and predictive algorithms that power strategic decision-making across the business. The ideal candidate will have a Master’s degree in a quantitative field, 4–6 years of hands-on experience, and demonstrated expertise in building models from linear regression to cutting-edge deep learning and large language models (LLMs). A Ph.D. is strongly preferred. Responsibilities Responsible for analyzing the data, identifying patterns, and do a detailed EDA. Build and refine predictive models using techniques such as linear/logistic regression, XGBoost, and neural networks. Leverage machine learning and NLP methods to analyze large-scale structured and unstructured datasets. Apply LLMs and transformers to develop solutions in content understanding, summarization, classification, and retrieval. Collaborate with data engineers and product teams to deploy scalable data pipelines and model production systems. Interpret model results, generate actionable insights, and present findings to technical and non-technical stakeholders. Stay abreast of the latest research and integrate cutting-edge techniques into ongoing projects Required Qualifications Master’s degree in Computer Science, Statistics, Applied Mathematics, or a related field. 4–6 years of industry experience in data science or machine learning roles. Strong statistical foundation, with practical experience in regression modeling, hypothesis testing, and A/B testing. Hands-on knowledge of: > Programming languages : Python (primary), SQL, R (optional) > Libraries : pandas, NumPy, scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, spaCy, Hugging Face Transformers > Distributed computing : PySpark, Dask > Big Data and Cloud Platforms : Databricks, AWS Sagemaker, Google Vertex AI, Azure ML > Data Engineering Tools : Apache Spark, Delta Lake, Airflow > ML Workflow & Visualization : MLflow, Weights & Biases, Plotly, Seaborn, Matplotlib > Version control and collaboration : Git, GitHub, Jupyter, VSCode Preferred Qualifications Masters or Ph.D. in a quantitative or technical field. Experience with deploying machine learning pipelines in production using CI/CD tools. Familiarity with containerization (Docker) and orchestration (Kubernetes) in ML workloads. Understanding of MLOps and model lifecycle management best practices. Experience in real-time data processing (Kafka, Flink) and high-throughput ML systems. What We Offer Competitive salary and performance bonuses Flexible working hours and remote options Opportunities for continued learning and research Collaborative, high-impact team environment Access to cutting-edge technology and compute resources To apply, send your resume to jobs@megovation.io to be part of a team pushing the boundaries of data-driven innovation. Show more Show less

Job description Job Title: Tech Lead (AI/ML) – Machine Learning & Generative AI Location: Nagpur (Hybrid / On-site) Experience: 8–15 years Employment Type: Full-time Job Summary: We are seeking a highly experienced Python Developer with a strong background in traditional Machine Learning and growing proficiency in Generative AI to join our AI Engineering team. This role is ideal for professionals who have delivered scalable ML solutions and are now expanding into LLM-based architectures, prompt engineering, and GenAI productization. You’ll be working at the forefront of applied AI, driving both model performance and business impact across diverse use cases. Key Responsibilities: Design and develop ML-powered solutions for use cases in classification, regression, recommendation, and NLP. Build and operationalize GenAI solutions, including fine-tuning, prompt design, and RAG implementations using models such as GPT, LLaMA, Claude, or Gemini. Develop and maintain FastAPI-based services that expose AI models through secure, scalable APIs. Lead data modeling, transformation, and end-to-end ML pipelines, from feature engineering to deployment. Integrate with relational (MySQL) and vector databases (e.g., ChromaDB, FAISS, Weaviate) to support semantic search, embedding stores, and LLM contexts. Mentor junior team members and review code, models, and system designs for robustness and maintainability. Collaborate with product, data science, and infrastructure teams to translate business needs into AI capabilities. Optimize model and API performance, ensuring high availability, security, and scalability in production environments. Core Skills & Experience: Strong Python programming skills with 5+ years of applied ML/AI experience. Demonstrated experience building and deploying models using TensorFlow, PyTorch, scikit-learn, or similar libraries. Practical knowledge of LLMs and GenAI frameworks, including Hugging Face, OpenAI, or custom transformer stacks. Proficient in REST API design using FastAPI and securing APIs in production environments. Deep understanding of MySQL (query performance, schema design, transactions). Hands-on with vector databases and embeddings for search, retrieval, and recommendation systems. Strong foundation in software engineering practices: version control (Git), testing, CI/CD. Preferred/Bonus Experience: Deployment of AI solutions on cloud platforms (AWS, GCP, Azure). Familiarity with MLOps tools (MLflow, Airflow, DVC, SageMaker, Vertex AI). Experience with Docker, Kubernetes, and container orchestration. Understanding of prompt engineering, tokenization, LangChain, or multi-agent orchestration frameworks. Exposure to enterprise-grade AI applications in BFSI, healthcare, or regulated industries is a plus. What We Offer: Opportunity to work on a cutting-edge AI stack integrating both classical ML and advanced GenAI. High autonomy and influence in architecting real-world AI solutions. A dynamic and collaborative environment focused on continuous learning and innovation. Show more Show less

Bangalore, Karnataka Factspan Overview: Factspan is a pure play data and analytics services organization. We partner with fortune 500 enterprises to build an analytics center of excellence, generating insights and solutions from raw data to solve business challenges, make strategic recommendations and implement new processes that help them succeed. With offices in Seattle, Washington and Bangalore, India; we use a global delivery model to service our customers. Our customers include industry leaders from Retail, Financial Services, Hospitality, and technology sectors. Job Description:  Engage with potential clients to understand their data science & analytics needs and challenges, acting as a trusted advisor  Craft innovative data science and AI solutions that address client’s needs  Design end-to-end AI/ML and advanced analytics architectures  Create compelling proposals and presentations that communicate our value proposition effectively  Present solutions to C-level executives and technical stakeholders, articulating business value and technical feasibility  Stay informed about emerging trends in AI/ML, deep learning, cloud computing, and modern data architectures to influence solution strategy  Partner with Product engineering, and delivery teams to ensure alignment between solutions and execution capabilities  Develop reusable frameworks, accelerators, best practices and participate in thought leadership activities Qualifications & Experience:  14+ years of experience in data science, AI/ML or enterprise analytics, with at least 5 years in solution architecture role  Proven expertise in designing and architecting AI/ML and data science solutions across modern cloud platforms (AWS, Azure, GCP) and big data ecosystems  Hands-on knowledge of AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn), data science platforms (Databricks, Snowflake, SageMaker), and data visualization tools  Strong understanding of MLOps, model governance, data governance, security, and compliance considerations  Excellent communication and presentation skills, with the ability to engage both technical and non-technical audiences  Strong problem-solving and adaptability skills with an ability to work independently and as part of a team Behavioral Skills:  Take ownership and accountability of outcomes, ensuring successful solution delivery and client satisfaction  Exhibit excellent written and verbal communication skills, effectively conveying complex information  Demonstrate strong problem-solving abilities, addressing challenges with innovative solutions  Foster a collaborative team environment and show self-driven initiative to achieve goals If you are passionate about leading teams to deliver impactful data science, AI/ML or analytics solutions, possess strong technical and consulting expertise, and are committed to achieving exceptional client satisfaction, we encourage you to apply for this exciting opportunity. Join us in driving innovation and delivering value to our clients through data-driven insights and solutions. Why Should You Apply? Buoyant Culture: Embark on an Grow with Us: Be part of a hyper- People: Join hands with the talent- ed, warm, collaborative team and highly exciting journey with a team that growth startup with ample accomplished leadership. innovates solutions everyday, opportunities to Learn & Innovate. tackles challenges head-on and crafts a vibrant work environment.

Job Title: Technical Lead – AI & LLMs Location: India (Remote or Hybrid as required) Employment Type: 12-Month Contract (Extendable) Compensation: Competitive, based on experience Team Size: Leading a team of 20 engineers About the Role We are looking for a Technical Lead with hands-on experience in Large Language Models (LLMs) , generative AI systems, and full-stack AI product development. In this contract role, you will be responsible for leading and coordinating a multidisciplinary team of 20 engineers to design, build, and deploy AI-driven solutions from concept to production. Key Responsibilities Architect and lead the development of AI-powered applications using LLMs and generative AI frameworks. Supervise model development, fine-tuning, prompt engineering, and RAG pipelines. Lead end-to-end implementation across data pipelines, backend APIs, and deployment infrastructure. Mentor a cross-functional team of machine learning engineers, backend developers, and DevOps specialists. Collaborate with stakeholders to align product requirements with technical deliverables. Set coding standards, enforce best practices, and ensure timely project delivery. Implement CI/CD and MLOps processes using tools like MLflow, SageMaker, or Vertex AI. Ensure scalability, security, and performance of deployed AI services. Required Skills 8+ years in software engineering, with at least 3+ years in AI/ML development. Proven experience working with LLMs, transformer models, and modern NLP frameworks. Proficient in Python , cloud services (AWS/GCP), RESTful APIs, and containerization (Docker/Kubernetes). Experience with LangChain, LlamaIndex, vector databases (FAISS, Pinecone, Weaviate), and orchestration tools. Demonstrated success in managing medium-to-large engineering teams and delivering AI products at scale. Strong communication, documentation, and leadership skills. Preferred Qualifications Experience working with open-source or commercial LLM providers (e.g., OpenAI, Mistral, Claude). Familiarity with frontend integration for AI interfaces (e.g., chatbot UIs, copilots). Awareness of AI safety, bias mitigation, and ethical deployment practices. Prior experience in startup or rapid innovation environments. Contract Details Duration: 12 months (with potential to extend) Location: India (remote-first with optional in-person meetings) Work Schedule: Full-time, flexible hours Reporting To: Partner of the company Show more Show less

About the Role You’ll join a small, fast team turning cutting-edge AI research into shippable products across text, vision, and multimodal domains. One sprint you’ll be distilling an LLM for WhatsApp chat-ops; the next you’ll be converting CAD drawings to BOM stories, or training a computer-vision model that flags onsite safety risks. You own the model life-cycle end-to-end: data prep ➞ fine-tune/distil ➞ evaluate ➞ deploy ➞ monitor. Key Responsibilities Model Engineering • Fine-tune and quantise open-weight LLMs (Llama 3, Mistral, Gemma) and SLMs for low-latency edge inference. • Train or adapt computer-vision models (YOLO, Segment Anything, SAM-DINO) to detect site hazards, drawings anomalies, or asset states. Multimodal Pipelines • Build retrieval-augmented-generation (RAG) stacks: loaders → vector DB (FAISS / OpenSearch) → ranking prompts. • Combine vision + language outputs into single “scene → story” responses for dashboards and WhatsApp bots. Serving & MLOps • Package models as Docker images, SageMaker endpoints, or ONNX edge bundles; expose FastAPI/GRPC handlers with auth, rate-limit, telemetry. • Automate CI/CD: GitHub Actions → Terraform → blue-green deploys. Evaluation & Guardrails • Design automatic eval harnesses (BLEU, BERTScore, CLIP similarity, toxicity & bias checks). • Monitor drift, hallucination, latency; implement rollback triggers. Enablement & Storytelling • Write prompt playbooks & model cards so other teams can reuse your work. • Run internal workshops: “From design drawing to narrative” / “LLM safety by example”. Required Skills & Experience 3+ yrs ML/NLP/CV in production; at least 1 yr hands-on with Generative AI . Strong Python (FastAPI, Pydantic, asyncio) and HuggingFace Transformers OR diffusers . Experience with minima­l-footprint models (LoRA, QLoRA, GGUF, INT-4) and vector search. Comfortable on AWS/GCP/Azure for GPU instances, serverless endpoints, IaC. Solid grasp of evaluation/guardrail frameworks (Helm, PromptLayer, Guardrails-AI, Triton metrics). Bonus Points Built a RAG or function-calling agent used by 500+ users. Prior CV pipeline (object-detection, segmentation) or speech-to-text real-time project. Live examples of creative prompt engineering or story-generation. Familiarity with LangChain, LlamaIndex, or BentoML. Why You’ll Love It Multidomain playground – text, vision, storytelling, decision-support. Tech freedom – pick the right model & stack; justify it; ship it. Remote-first – work anywhere ±4 hrs of IST; quarterly hack-weeks in Hyderabad. Top-quartile pay – base + milestone bonus + conference stipend. How to Apply Send a resume and link to GitHub / HF / Kaggle showcasing LLM or CV work. Include a 200-word note describing your favourite prompt or model tweak and the impact it had. Short-listed candidates complete a practical take-home (fine-tune tiny model, build RAG or vision demo, brief write-up) and a 45-min technical chat. We hire builders, not resume keywords. Show us you can ship AI that works in the real world—and explain it clearly—and you’re in. Show more Show less

Job Title : AI/ML Engineer & Large Language Models (LLM) Location : Bengaluru, India Experience : 1 - 3 years Position Summary We are looking for an AI/ML Engineer with a strong background in Python, Django, and Object-Oriented Programming (OOP). The ideal candidate should have significant experience in prompt engineering, open source model fine-tuning, and using the HuggingFace libraries. Additionally, expertise in working with cloud platforms such as AWS SageMaker or similar services for training AI models is essential. Priority will be given to candidates with a research background, particularly those who have successfully fine-tuned and deployed AI models in real-world applications. Key Responsibilities Develop, fine-tune, and deploy AI models using Python and Django frameworks. Apply prompt engineering techniques to optimize model outputs and improve accuracy. Utilize HuggingFace libraries and other ML tools to build and fine-tune state-of-the-art models. Work on cloud platforms like AWS SageMaker or equivalent to train and deploy AI models efficiently. Collaborate with research teams to translate cutting-edge AI research into scalable solutions. Implement object-oriented programming (OOP) principles and problem-solving strategies in developing AI solutions. Stay updated with the latest advancements in AI/ML and integrate new techniques into ongoing projects. Document and share findings, best practices, and solutions across the engineering team. An Ideal Candidate Will Have Strong proficiency in Python and Flask/FastAPI. Experience in prompt engineering and fine-tuning AI models. Extensive experience with HuggingFace libraries and similar AI/ML tools. Strong experience in AI Agentic Architecture Hands-on experience with cloud platforms such as AWS SageMaker for training and deploying models. Proficiency in Databases like MongoDB or PostgreSQL, as well as vector databases such as FAISS, Qdrant, or Elasticsearch Hands-on experience with Docker and Git for version control. Background in AI/ML research, with a preference for candidates from research institutes. Demonstrated experience in training and deploying machine learning models in real-world applications. Solid understanding of object-oriented programming and problem-solving skills. Strong analytical skills and the ability to work independently or in a team environment. Excellent communication skills, with the ability to present complex technical concepts to non-technical stakeholders. Must Have Skills Python Object-Oriented Programming (OOP) Prompt engineering HuggingFace libraries and similar AI/ML tools Open Source Model fine-tuning AI Agentic Architecture such as LangGraph and CrewA Docker and Git for version control. Databases like MongoDB or PostgreSQL, as well as vector databases such as FAISS, Qdrant, or Elasticsearch Good To Have Deep Learning and Machine Learning AWS SageMaker or similar services for training AI models Previous experience in academic or industrial research, with published work in AI/ML. Proven track record of successful AI model deployments and optimizations. Experience with databases like MongoDB or PostgreSQL, as well as vector databases such as FAISS, Qdrant, or Elasticsearch. Perks & Benefits Work on groundbreaking AI/ML projects in a collaborative and innovative environment. Access to state-of-the-art tools and cloud platforms. Opportunities for professional development and continuous learning. Competitive salary. (ref:hirist.tech) Show more Show less

Comcast brings together the best in media and technology. We drive innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines. We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring cutting-edge products and services to life for millions of customers every day. If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at Comcast. Job Summary Responsible for extracting knowledge and insights from high volume, high dimensional data in order to investigate complex business problems through a range of data preparation, modeling, analysis and/or visualization techniques, which may include the use of advanced statistical analysis, algorithms, predictive modeling, experimentation and pattern recognition to create solutions that enable enhanced business performance. Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement. The team is composed of experts in artificial intelligence, deep learning, data-structures, algorithms, distributed systems, and system performance and analysis. The systems that the team builds get used across the multitude of Company data science-based services and deployments. Integrates knowledge of business and functional priorities. Acts as a key contributor in a complex and crucial environment. May lead teams or projects and shares expertise. Job Description Core Responsibilities Core Responsibilities You have experience with GitHub and with one or more ML cloud compute solutions: AWS SageMaker, Microsoft Azure, Google Cloud, Kubeflow, Databricks, etc. Excellent Communication skills with both US team and the team in India You are a lifelong learner, who is driven by curiosity and a desire to make a positive impact in the organization. You are results-driven, possess business acumen, and an ability to communicate your work and your findings. You are an engineer/manager at heart with an analytical mindset, but with a keen sense of serving the business. You have advanced capabilities in Excel, PowerPoint, SQL, and Python to conduct analyses, build models, and present findings. You have excellent project management, organizational, and collaboration skills. You enjoy working in global teams, assisting and educating less experienced members, while also learning from more senior colleagues. You take initiative and have the ability to drive projects to completion at each phase of the process, from ideation to data acquisition, to engaging with stakeholders, to developing the models, to evaluating and fine-tuning their performance, to productionizing solutions via ML pipelines, to building model performance reports. Knowledge of how supply and demand best practice business and data processes generate business value. Including, but not limited to demand forecasting, inventory management, supply planning, Sales and Operations Planning, and replenishment planning. Demonstrated excellent track record of innovative and effective applications of data science principles, technology, and techniques to solve business problems efficiently. Knowledge of and experience with best practice demand management metrics; forecast accuracy, demand attainment, bias, planner value add. Intelligence, integrity, domain knowledge, and verbal agility that allows you to earn the trust of business and technical teams across the company. Excellent operational and managerial skills required, with a proven track record of successful management of complex, data driven demand forecasting, logistics, supply chain, & operations. The successful candidate will have multiple years of consumer goods retail environment, utilizing advanced modeling techniques as a basis to drive results. A strong analytical & data mindset is essential for this position. Flexible to work and support team with extended time/shifts when and where required. Required Skillset Should be an effective and prolific doer but should also be a creative thinker who likes to operate outside the box and suggest alternative solutions. Should have experience in developing Forecasting models and understand Demand Planning processes. Understand optimization models, techniques and tools (Gurobi, Coupa, etc.) Experience in Network optimization / Transportation opt Experience in Data science, machine learning or optimization models (linear programming) Experience in Python, SQL or R for model development Knowledgeable in handling large set of data, databases, data warehouse design, cloud storage and ETL best practices. Experience with BI tools like PowerBI and Tableau Experience in data pipelines developments and systems such as SQL, Maria DB etc.. Preferred Requirements Experience in data science/ops research experience preferably within the supply chain / logistics industry, demand planning, CPG industry and/or retail replenishment. Master’s Degree in Statistics, Operations Research, Data Science, Computer Science or related field is a plus. Experience in supply chain planning systems and their data science capabilities like 09 Solutions, SAP, Blue Yonder or other top tier solutions a plus Knowledge of and experience with leading data reporting applications including Tableau, Power BI, QlikView, etc. is a plu Comcast is proud to be an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law. Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality – to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details. Education Master's Degree While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience. Relevant Work Experience 7-10 Years Show more Show less

Job Description Key Responsibilities Hands-on Development Develop and implement machine learning models and algorithms, including supervised, unsupervised, deep learning, and reinforcement learning techniques. Implement Generative AI solutions using technologies like RAG (Retrieval-Augmented Generation), Vector DBs, and frameworks such as LangChain and Hugging Face, Agentic Ai. Utilize popular AI/ML frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn. Design and deploy NLP models and techniques, including text classification, RNNs, CNNs, and Transformer-based models like BERT. Ensure robust end-to-end AI/ML solutions, from data preprocessing and feature engineering to model deployment and monitoring. Technical Proficiency Demonstrate strong programming skills in languages commonly used for data science and ML, particularly Python. Leverage cloud platforms and services for AI/ML, especially AWS, with knowledge of AWS Sagemaker, Lambda, DynamoDB, S3, and other AWS resources. Mentorship Mentor and coach a team of data scientists and machine learning engineers, fostering skill development and professional growth. Provide technical guidance and support, helping team members overcome challenges and achieve project goals. Set technical direction and strategy for AI/ML projects, ensuring alignment with business goals and objectives. Facilitate knowledge sharing and collaboration within the team, promoting best practices and continuous learning. Strategic Advisory Collaborate with cross-functional teams to integrate AI/ML solutions into business processes and products. Provide strategic insights and recommendations to support decision-making processes. Communicate effectively with stakeholders at various levels, including technical and non-technical audiences. Qualifications Bachelor’s degree in a relevant field (e.g., Computer Science) or equivalent combination of education and experience. Typically, 8-10 years of relevant work experience in AI/ML/GenAI 15+ years of overall work experience. With proven ability to manage projects and activities. Extensive experience with generative AI technologies, including RAG, Vector DBs, and frameworks such as LangChain and Hugging Face, Agentic AI Proficiency in machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning. Extensive experience with AI/ML frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn. Strong knowledge of natural language processing (NLP) techniques and models, including Transformer-based models like BERT. Proficient programming skills in Python and experience with cloud platforms like AWS. Experience with AWS Cloud Resources, including AWS Sagemaker, Lambda, DynamoDB, S3, etc., is a plus. Proven experience leading a team of data scientists or machine learning engineers on complex projects. Strong project management skills, with the ability to prioritize tasks, allocate resources, and meet deadlines. Excellent communication skills and the ability to convey complex technical concepts to diverse audiences. Preferred Qualifications Experience in setting technical direction and strategy for AI/ML projects. Experience in the Insurance domain Ability to mentor and coach junior team members, fostering growth and development. Proven track record of successfully managing AI/ML projects from conception to deployment. At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We’re committed to fostering an inclusive environment where everyone can thrive. Recruitment fraud is a scheme in which fictitious job opportunities are offered to job seekers typically through online services, such as false websites, or through unsolicited emails claiming to be from the company. These emails may request recipients to provide personal information or to make payments as part of their illegitimate recruiting process. DXC does not make offers of employment via social media networks and DXC never asks for any money or payments from applicants at any point in the recruitment process, nor ask a job seeker to purchase IT or other equipment on our behalf. More information on employment scams is available here . Show more Show less

Job Category: AIML Job Type: Full Time Job Location: Bengaluru Mangalore Experience: 4-8 Years Skills: AI AWS/AZURE/GCP Azure ML C computer vision data analytics Data Modeling Data Visualization deep learning Descriptive Analytics GenAI Image processing Java LLM models ML ONNX Predictive Analytics Python R Regression/Classification Models SageMaker SQL TensorFlow Position Overview We are looking for an experienced AI/ML Engineer to join our team in Bengaluru. The ideal candidate will bring a deep understanding of machine learning, artificial intelligence, and big data technologies, with proven expertise in developing scalable AI/ML solutions. You will lead technical efforts, mentor team members, and collaborate with cross-functional teams to design, develop, and deploy cutting edge AI/ML applications. Job Details Job Category: AI/ML Engineer. Job Type: Full-Time Job Location: Bengaluru Experience Required: 4-8 Years About Us We are a multi-award-winning creative engineering company. Since 2011, we have worked with our customers as a design and technology enablement partner, guiding them on their digital transformation journeys. Roles And Responsibilities Design, develop, and deploy deep learning models for object classification, detection, and segmentation using CNNs and Transfer Learning. Implement image preprocessing and advanced computer vision pipelines. Optimize deep learning models using pruning, quantization, and ONNX for deployment on edge devices. Work with PyTorch, TensorFlow, and ONNX frameworks to develop and convert models. Accelerate model inference using GPU programming with CUDA and cuDNN. Port and test models on embedded and edge hardware platforms. ( Orin, Jetson, Hailo ) Conduct research and experiments to evaluate and integrate GenAI technologies in computer vision tasks. Explore and implement cloud-based AI workflows, particularly using AWS/Azure AI/ML services. Collaborate with cross-functional teams for data analytics, data processing, and large-scale model training. Required Skills Strong programming experience in Python. Solid background in deep learning, CNNs, and transfer learning and Machine learning basics. Expertise in object detection, classification, segmentation. Proficiency with PyTorch, TensorFlow, and ONNX. Experience with GPU acceleration (CUDA, cuDNN). Hands-on knowledge of model optimization (pruning, quantization). Experience deploying models to edge devices (e.g., Jetson, mobile, Orin, Hailo ) Understanding of image processing techniques. Familiarity with data pipelines, data preprocessing, and data analytics. Willingness to explore and contribute to Generative AI and cloud-based AI solutions. Good problem-solving and communication skills. Preferred (Nice-to-Have) Experience with C/C++. Familiarity with AWS Cloud AI/ML tools (e.g., SageMaker, Rekognition). Exposure to GenAI frameworks like OpenAI, Stable Diffusion, etc. Knowledge of real-time deployment systems and streaming analytics. Qualifications Graduation/Post-graduation in Computers, Engineering, or Statistics from a reputed institute. What We Offer Competitive salary and benefits package. Opportunity to work in a dynamic and innovative environment. Professional development and learning opportunities. Visit us on: CodeCraft Technologies LinkedIn : CodeCraft Technologies LinkedIn Instagram : CodeCraft Technologies Instagram Show more Show less

Develop and deploy ML models using SageMaker. Automate data pipelines and training processes. Monitor and optimize model performance. Ensure model governance and reproducibility.

Website http://www.intraedge.com Machine Leaning Engineer Experience-6+Years Notice period-max 15 days Location -Pune/Remote Job Summary: Job Overview Machine Learning Engineer (Python, AWS) We are seeking an experienced Machine Learning Engineer with 5+ years of hands-on experience in developing and deploying ML solutions. The ideal candidate will have strong Python programming skills and a proven track record working with AWS services for machine learning. Responsibilities: Design, develop, and deploy scalable machine learning models. Implement and optimize ML algorithms using Python. Leverage AWS services (e.g., Sagemaker, EC2, S3, Lambda) for ML model training, deployment, and monitoring. Collaborate with data scientists and other engineers to bring ML solutions to production. Ensure the performance, reliability, and scalability of ML systems. Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 5+ years of professional experience as a Machine Learning Engineer. Expertise in Python programming for machine learning. Strong experience with AWS services for ML (SageMaker, EC2, S3, Lambda, etc.). Solid understanding of machine learning algorithms and principles. Experience with MLOps practices is a plus. Show more Show less

Role – AIML Data Scientist Location : Kochi Job Description Be a hands on problem solver with consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges Use the knowledge of wide variety of AI/ML techniques and algorithms to find what combinations of these techniques can best solve the problem Improve Model accuracy to deliver greater business impact Estimate business impact due to deployment of model Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines 4. Design , develop & deploy Deep learning models using Tensorflow / Pytorch Experience in using Deep learning models with text, speech, image and video data Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etc Design and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCV Knowledge of State of the art Deep learning algorithms Optimize and tune Deep Learnings model for best possible accuracy Use visualization tools/modules to be able to explore and analyze outcomes & for Model validation eg: using Power BI / Tableau Work with application teams, in deploying models on cloud as a service or on-prem Deployment of models in Test / Control framework for tracking Build CI/CD pipelines for ML model deployment Integrating AI&ML models with other applications using REST APIs and other connector technologies Constantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact. Technology/Subject Matter Expertise Sufficient expertise in machine learning, mathematical and statistical sciences Use of versioning & Collaborative tools like Git / Github Good understanding of landscape of AI solutions – cloud, GPU based compute, data security and privacy, API gateways, microservices based architecture, big data ingestion, storage and processing, CUDA Programming Develop prototype level ideas into a solution that can scale to industrial grade strength Ability to quantify & estimate the impact of ML models Softskills Profile Curiosity to think in fresh and unique ways with the intent of breaking new ground. Must have the ability to share, explain and “sell” their thoughts, processes, ideas and opinions, even outside their own span of control Ability to think ahead, and anticipate the needs for solving the problem will be important Ability to communicate key messages effectively, and articulate strong opinions in large forums Desirable Experience: Keen contributor to open source communities, and communities like Kaggle Ability to process Huge amount of Data using Pyspark/Hadoop Development & Application of Reinforcement Learning Knowledge of Optimization/Genetic Algorithms Operationalizing Deep learning model for a customer and understanding nuances of scaling such models in real scenarios Optimize and tune deep learning model for best possible accuracy Understanding of stream data processing, RPA, edge computing, AR/VR etc Appreciation of digital ethics, data privacy will be important Experience of working with AI & Cognitive services platforms like Azure ML, IBM Watson, AWS Sagemaker, Google Cloud will all be a big plus Experience in platforms like Data robot, Cognitive scale, H2O.AI etc will all be a big plus Show more Show less

This role is for one of our clients Industry: Technology, Information and Media Seniority level: Mid-Senior level Min Experience: 3 years Location: Bengaluru JobType: full-time We are on the lookout for a Machine Intelligence Specialist to join our forward-thinking engineering team. This role is ideal for individuals passionate about building intelligent systems that transform raw data into real-world automation through advanced natural language processing (NLP), computer vision, and machine learning technologies. You will lead initiatives involving deep learning, model deployment, and system optimization, contributing to high-impact products across domains. If you're energized by turning cutting-edge AI research into practical solutions, this is your opportunity to make a difference. Your Mission Design and Develop Intelligent Systems : Create robust machine learning models for tasks in NLP (e.g., text summarization, named entity recognition, semantic search) and computer vision (e.g., image classification, OCR, object detection). Deep Learning Engineering : Build and optimize models using TensorFlow, Keras, or PyTorch, leveraging neural architectures such as CNNs, RNNs, LSTMs, and Transformers. Collaborative Innovation : Partner with product, data, and engineering teams to align AI development with real business needs, ensuring seamless integration of intelligence into products and workflows. Cloud-Native Deployment : Implement and scale ML models on AWS, Azure, or GCP using native services and containerization tools (Docker, Kubernetes). AI at Scale : Drive performance tuning, data preprocessing, A/B testing, and continuous training to ensure accuracy and production reliability. Model Lifecycle Ownership : Implement MLOps best practices, including CI/CD pipelines for ML, model versioning, and monitoring using tools like MLflow or SageMaker. Ethical & Transparent AI : Prioritize explainability, fairness, and compliance throughout the model development lifecycle. What You Bring Essential Qualifications 3+ years of hands-on experience in designing, training, and deploying machine learning models. Strong background in Python and ML libraries: TensorFlow, Keras, OpenCV, scikit-learn, Hugging Face Transformers, etc. Experience in both NLP and computer vision use cases and toolkits. Proven ability to deploy models using cloud-native AI tools on AWS, Azure, or GCP. Familiarity with containerization (Docker) and orchestration (Kubernetes). Solid foundation in mathematics, statistics, and deep learning algorithms. Excellent communication skills and a collaborative mindset. Bonus Points For Experience with MLOps workflows and tools like MLflow, TFX, or Kubeflow. Exposure to edge AI or streaming inference systems. Understanding of responsible AI principles and data governance. Show more Show less

We are united in our mission to make a positive impact on healthcare. Join Us! South Florida Business Journal, Best Places to Work 2024 Inc. 5000 Fastest-Growing Private Companies in America 2024 2024 Black Book Awards, ranked #1 EHR in 11 Specialties 2024 Spring Digital Health Awards, “Web-based Digital Health” category for EMA Health Records (Gold) 2024 Stevie American Business Award (Silver), New Product and Service: Health Technology Solution (Klara) Who We Are We Are Modernizing Medicine (WAMM)! We’re a team of bright, passionate, and positive problem-solvers on a mission to place doctors and patients at the center of care through an intelligent, specialty-specific cloud platform. Our vision is a world where the software we build increases medical practice success and improves patient outcomes. Founded in 2010 by Daniel Cane and Dr. Michael Sherling, we have grown to over 3400 combined direct and contingent team members serving eleven specialties, and we are just getting started! ModMed is based in Boca Raton, FL, with office locations in Santiago, Chile, Berlin, Germany, Hyderabad, India, and a robust remote workforce with team members across the US. ModMed is hiring a driven ML Ops Engineer 2 to join our positive, passionate, and high-performing team focused on scalable ML Systems. This is an exciting opportunity to You as you will collaborate with data scientists, engineers, and other cross-functional teams to ensure seamless model deployment, monitoring, and automation. If you're passionate about cloud infrastructure, automation, and optimizing ML pipelines, this is the role for you within a fast-paced Healthcare IT company that is truly Modernizing Medicine! Key Responsibilities Model Deployment & Automation: Develop, deploy, and manage ML models on Databricks using MLflow for tracking experiments, managing models, and registering them in a centralized repository. Infrastructure & Environment Management: Set up scalable and fault-tolerant infrastructure to support model training and inference in cloud environments such as AWS, GCP, or Azure. Monitoring & Performance Optimization: Implement monitoring systems to track model performance, accuracy, and drift over time. Create automated systems for re-training and continuous learning to maintain optimal performance. Data Pipeline Integration: Collaborate with the data engineering team to integrate model pipelines with real-time and batch data processing frameworks, ensuring seamless data flow for training and inference. Skillset & Qualification Model Deployment: Experience with deploying models in production using cloud platforms like AWS Sagemaker, GCP AI Platform, or Azure ML Studio. Version Control & Automation: Experience with MLOps tools such as MLflow, Kubeflow, or Airflow to automate and monitor the lifecycle of machine learning models. Cloud Expertise: Experience with cloud-based machine learning services on AWS, Google Cloud, or Azure, ensuring that models are scalable and efficient. Engineers must be skilled in measuring and optimizing model performance through metrics like AUC, precision, recall, and F1-score, ensuring that models are robust and reliable in production settings. Education: Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, or a related technical field. ModMed In India Benefit Highlights High growth, collaborative, transparent, fun, and award-winning culture Comprehensive benefits package including medical for you, your family, and your dependent parents The company supported community engagement opportunities along with a paid Voluntary Time Off day to use for volunteering in your community of interest Global presence, and in-person collaboration opportunities; dog-friendly HQ (US), Hybrid office-based roles and remote availability Company-sponsored Employee Resource Groups that provide engaged and supportive communities within ModMed ModMed Benefits Highlight: At ModMed, we believe it’s important to offer a competitive benefits package designed to meet the diverse needs of our growing workforce. Eligible Modernizers can enroll in a wide range of benefits: India Meals & Snacks: Enjoy complimentary office lunches & dinners on select days and healthy snacks delivered to your desk, Insurance Coverage: Comprehensive health, accidental, and life insurance plans, including coverage for family members, all at no cost to employees, Allowances: Annual wellness allowance to support your well-being and productivity, Earned, casual, and sick leaves to maintain a healthy work-life balance, Bereavement leave for difficult times and extended medical leave options, Paid parental leaves, including maternity, paternity, adoption, surrogacy, and abortion leave, Celebration leave to make your special day even more memorable, and company-paid holidays to recharge and unwind. United States Comprehensive medical, dental, and vision benefits, including a company Health Savings Account contribution, 401(k): ModMed provides a matching contribution each payday of 50% of your contribution deferred on up to 6% of your compensation. After one year of employment with ModMed, 100% of any matching contribution you receive is yours to keep. Generous Paid Time Off and Paid Parental Leave programs, Company paid Life and Disability benefits, Flexible Spending Account, and Employee Assistance Programs, Company-sponsored Business Resource & Special Interest Groups that provide engaged and supportive communities within ModMed, Professional development opportunities, including tuition reimbursement programs and unlimited access to LinkedIn Learning, Global presence and in-person collaboration opportunities; dog-friendly HQ (US), Hybrid office-based roles and remote availability for some roles, Weekly catered breakfast and lunch, treadmill workstations, Zen, and wellness rooms within our BRIC headquarters. PHISHING SCAM WARNING: ModMed is among several companies recently made aware of a phishing scam involving imposters posing as hiring managers recruiting via email, text and social media. The imposters are creating misleading email accounts, conducting remote "interviews," and making fake job offers in order to collect personal and financial information from unsuspecting individuals. Please be aware that no job offers will be made from ModMed without a formal interview process, and valid communications from our hiring team will come from our employees with a ModMed email address (first.lastname@modmed.com). Please check senders’ email addresses carefully. Additionally, ModMed will not ask you to purchase equipment or supplies as part of your onboarding process. If you are receiving communications as described above, please report them to the FTC website. Show more Show less

Years of exp : 10 - 15 yrs Location : Noida Join us as Cloud Engineer at Dailoqa , where you will be responsible for operationalizing cutting-edge machine learning and generative AI solutions, ensuring scalable, secure, and efficient deployment across infrastructure. You will work closely with data scientists, ML engineers, and business stakeholders to build and maintain robust MLOps pipelines, enabling rapid experimentation and reliable production implementation of AI models, including LLMs and real-time analytics systems. To be successful as Cloud Engineer you should have experience with: Cloud sourcing, networks, VMs, performance, scaling, availability, storage, security, access management Deep expertise in one or more cloud platforms: AWS, Azure, GCP Strong experience in containerization and orchestration (Docker, Kubernetes, Helm) Familiarity with CI/CD tools: GitHub Actions, Jenkins, Azure DevOps, ArgoCD, etc. Proficiency in scripting languages (Python, Bash, PowerShell) Knowledge of MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML Strong understanding of DevOps principles applied to ML workflows. Key Responsibilities may include: Design and implement scalable, cost-optimized, and secure infrastructure for AI-driven platforms. Implement infrastructure as code using tools like Terraform, ARM, or Cloud Formation. Automate infrastructure provisioning, CI/CD pipelines, and model deployment workflows. Ensure version control, repeatability, and compliance across all infrastructure components. Set up monitoring, logging, and alerting frameworks using tools like Prometheus, Grafana, ELK, or Azure Monitor. Optimize performance and resource utilization of AI workloads including GPU-based training/inference Experience with Snowflake, Databricks for collaborative ML development and scalable data processing. Understanding model interpretability, responsible AI, and governance. Contributions to open-source MLOps tools or communities. Strong leadership, communication, and cross-functional collaboration skills. Knowledge of data privacy, model governance, and regulatory compliance in AI systems. Exposure to LangChain, Vector DBs (e. g. , FAISS, Pinecone), and retrieval-augmented generation (RAG) pipelines. Show more Show less

Job Description: We are seeking a Data Scientist with strong experience in Artificial Intelligence (AI), Machine Learning (ML), AWS cloud services, Big Data technologies, and Python programming. You will work on building and deploying data-driven solutions that solve real-world problems, enhance decision-making, and drive business value. Key Responsibilities: Develop and implement machine learning models and AI solutions for business use cases Work with large datasets using Big Data tools for data processing, transformation, and analysis Design, build, and deploy models on AWS cloud infrastructure Collaborate with data engineers, analysts, and product teams to understand requirements and deliver insights Communicate results and recommendations to technical and non-technical stakeholders Continuously evaluate and improve the performance of existing models Required Skills: Strong proficiency in Python and popular ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch, Pandas) Hands-on experience with AWS services (S3, EC2, SageMaker, Lambda, etc.) Experience with Big Data tools such as Spark, Hadoop, or similar Show more Show less

Job Description: We are seeking a Data Scientist with strong expertise in AI/ML, AWS, Big Data, and Python to join our data-driven team. You will design, build, and deploy scalable machine learning models and data pipelines that drive key business decisions. Key Responsibilities: Develop and implement machine learning models for classification, regression, clustering, and forecasting. Work with large-scale structured and unstructured data using Big Data tools (e.g., Spark, Hadoop). Build data pipelines and deploy models on AWS cloud services (e.g., S3, SageMaker, Lambda, EMR). Conduct exploratory data analysis and feature engineering using Python (NumPy, Pandas, Scikit-learn, etc.). Collaborate with engineering, product, and analytics teams to integrate models into production systems. Continuously improve model accuracy and performance through testing and experimentation. Required Skills: Strong programming skills in Python and experience with ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch). Experience with AWS services for data processing and model deployment. Familiarity with Big Data technologies like Hadoop, Spark, Hive, or similar. Show more Show less

A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. As part of our Analytics and Insights Consumption team, you’ll analyze data to drive useful insights for clients to address core business issues or to drive strategic outcomes. You'll use visualization, statistical and analytics models, AI/ML techniques, Modelops and other techniques to develop these insights. Years of Experience: Candidates with 4+ years of hands on experience Must Have Internal & External stakeholder management Familiarity with the CCaaS domain, CCaaS Application Development , contact center solution design & presales consulting. In-depth knowledge of CCaaS platforms like MS DCCP, Amazon Connect, NICECXOne, Genesys Cloud , Cisco Webex CC, Cisco HCS, UCCE/PCCE etc., including their architecture, functionalities, and application development, integration capabilities Governance & communication skills Hands-on configuration of Gen AI, LLM to be built on top of CCaaS platforms/Domain (MS DCCP, Amazon Connect, Genesys Cloud/NICE CX) includes, Develop and implement generative AI models to enhance customer interactions, including chatbots, virtual agents, and automated response systems. Speech scientist & speech, conversational fine-tuning (grammar & pattern analysis) Collaborate with stakeholders to identify business needs and define AI-driven solutions that improve customer experiences. Analyze existing customer service processes and workflows to identify areas for AI integration and optimization. Create and maintain documentation for AI solutions, including design specifications and user guides. Monitor and evaluate the performance of AI models, making adjustments as necessary to improve accuracy and effectiveness. Stay updated on the latest advancements in AI technologies and their applications in customer service and contact centers. Conduct training sessions for team members and stakeholders on the use and benefits of AI technologies in the contact center. Understanding of the fundamental ingredients of enterprise integration including interface definitions and contracts; REST APIs or SOAP web services; SQL,MY SQL, Oracle , PostgreSQL , Dynamo DB, S3, RDS Provide effective real time demonstrations of CCaaS & AI (Bots) platforms High proficiency in defining top notch customer facing slides/presentations Gen AI,LLM platforms MUST have technologies includes Copilot, Copilot Studio, Amazon Bedrock, Amazon Titan, Sagemaker, Azure OpenAI, Azure AI Services, Google Vertex AI, Gemini AI. Proficiency in data visualization tools like Tableau, Power BI, Quicksight and others Nice To Have Experience in CPaaS platforms (Twilio, Infobip) for synergies between Communication Platform As A Service & Contact Center As a Service Understanding of cloud platforms (e.g., AWS, Azure, Google Cloud) and their services for scalable data storage, processing, and analytics Work on high velocity Presales solution consulting engagements (RFP, RFI, RFQ) Define industry specific use cases (BFS & I, Telecom, Retail, Manlog etc) Work on high volume presales consulting engagements including solution design document definition, commercial construct (CCaaS) Defining Business Case Show more Show less

Job Description: Key Responsibilities Hands-on Development: Develop and implement machine learning models and algorithms, including supervised, unsupervised, deep learning, and reinforcement learning techniques. Implement Generative AI solutions using technologies like RAG (Retrieval-Augmented Generation), Vector DBs, and frameworks such as LangChain and Hugging Face, Agentic Ai. Utilize popular AI/ML frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn. Design and deploy NLP models and techniques, including text classification, RNNs, CNNs, and Transformer-based models like BERT. Ensure robust end-to-end AI/ML solutions, from data preprocessing and feature engineering to model deployment and monitoring. Technical Proficiency: Demonstrate strong programming skills in languages commonly used for data science and ML, particularly Python. Leverage cloud platforms and services for AI/ML, especially AWS, with knowledge of AWS Sagemaker, Lambda, DynamoDB, S3, and other AWS resources. Mentorship: Mentor and coach a team of data scientists and machine learning engineers, fostering skill development and professional growth. Provide technical guidance and support, helping team members overcome challenges and achieve project goals. Set technical direction and strategy for AI/ML projects, ensuring alignment with business goals and objectives. Facilitate knowledge sharing and collaboration within the team, promoting best practices and continuous learning. Strategic Advisory: Collaborate with cross-functional teams to integrate AI/ML solutions into business processes and products. Provide strategic insights and recommendations to support decision-making processes. Communicate effectively with stakeholders at various levels, including technical and non-technical audiences. Qualifications Bachelor’s degree in a relevant field (e.g., Computer Science) or equivalent combination of education and experience. Typically, 8-10 years of relevant work experience in AI/ML/GenAI 15+ years of overall work experience. With proven ability to manage projects and activities. Extensive experience with generative AI technologies, including RAG, Vector DBs, and frameworks such as LangChain and Hugging Face, Agentic AI Proficiency in machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning. Extensive experience with AI/ML frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn. Strong knowledge of natural language processing (NLP) techniques and models, including Transformer-based models like BERT. Proficient programming skills in Python and experience with cloud platforms like AWS. Experience with AWS Cloud Resources, including AWS Sagemaker, Lambda, DynamoDB, S3, etc., is a plus. Proven experience leading a team of data scientists or machine learning engineers on complex projects. Strong project management skills, with the ability to prioritize tasks, allocate resources, and meet deadlines. Excellent communication skills and the ability to convey complex technical concepts to diverse audiences. Preferred Qualifications Experience in setting technical direction and strategy for AI/ML projects. Experience in the Insurance domain Ability to mentor and coach junior team members, fostering growth and development. Proven track record of successfully managing AI/ML projects from conception to deployment. Recruitment fraud is a scheme in which fictitious job opportunities are offered to job seekers typically through online services, such as false websites, or through unsolicited emails claiming to be from the company. These emails may request recipients to provide personal information or to make payments as part of their illegitimate recruiting process. DXC does not make offers of employment via social media networks and DXC never asks for any money or payments from applicants at any point in the recruitment process, nor ask a job seeker to purchase IT or other equipment on our behalf. More information on employment scams is available here .

Job Summary: We are seeking a highly skilled and experienced Data Scientist with a deep understanding of data analytics powered by artificial intelligence (AI) tools. The ideal candidate will be passionate about turning data into actionable insights using cutting-edge AI platforms, automation techniques, and advanced statistical methods. Key Responsibilities: Develop and deploy scalable AI-powered data analytics solutions for business intelligence, forecasting, and optimization. Leverage AI tools to automate data cleansing, feature engineering, model building, and visualization. Design and conduct advanced statistical analyses and machine learning models (supervised, unsupervised, NLP, etc.). Collaborate cross-functionally with engineering and business teams to drive data-first decision-making. Must-Have Skills & Qualifications: Minimum 4 years of professional experience in data science, analytics, or a related field. Proficiency in Python and/or R with strong hands-on experience in ML libraries (scikit-learn, XGBoost, TensorFlow, etc.). Expert knowledge of SQL and working with relational databases. Proven experience with data wrangling, data pipelines, and ETL processes. Deep Understanding of AI Tools for Data Analytics (Experience with several of the following is required): Data Preparation & Automation: Alteryx, Trifacta, KNIME AI/ML Platforms: DataRobot, H2O.ai, Amazon SageMaker, Azure ML Studio, Google Vertex AI Visualization & BI: Tableau, Power BI, Looker (with AI/ML integrations) AutoML & Predictive Modeling: Google AutoML, IBM Watson Studio, BigML NLP & Text Analytics: OpenAI (ChatGPT, Codex APIs), Hugging Face Transformers, MonkeyLearn Workflow Orchestration: Apache Airflow, Prefect Preferred Qualifications: Degree in Computer Science, Data Science, Statistics, or related field. Experience in cloud-based environments (AWS, GCP, Azure) for ML workloads. To apply, please send your resume to sooraj@superpe.in or shreya@superpe.in SuperPe is an equal opportunity employer and welcomes candidates of all backgrounds to apply. We look forward to hearing from you! Show more Show less

CACI India, RMZ Nexity, Tower 30 4th Floor Survey No.83/1, Knowledge City Raidurg Village, Silpa Gram Craft Village, Madhapur, Serilingampalle (M), Hyderabad, Telangana 500081, India Req #1097 02 May 2025 CACI International Inc is an American multinational professional services and information technology company headquartered in Northern Virginia. CACI provides expertise and technology to enterprise and mission customers in support of national security missions and government transformation for defense, intelligence, and civilian customers. CACI has approximately 23,000 employees worldwide. Headquartered in London, CACI Ltd is a wholly owned subsidiary of CACI International Inc., a publicly listed company on the NYSE with annual revenue in excess of US $6.2bn. Founded in 2022, CACI India is an exciting, growing and progressive business unit of CACI Ltd. CACI Ltd currently has over 2000 intelligent professionals and are now adding many more from our Hyderabad and Pune offices. Through a rigorous emphasis on quality, the CACI India has grown considerably to become one of the UKs most well-respected Technology centres. About Data Platform The Data Platform will be built and managed “as a Product” to support a Data Mesh organization. The Data Platform focusses on enabling decentralized management, processing, analysis and delivery of data, while enforcing corporate wide federated governance on data, and project environments across business domains. The goal is to empower multiple teams to create and manage high integrity data and data products that are analytics and AI ready, and consumed internally and externally. What does a Data Infrastructure Engineer do? A Data Infrastructure Engineer will be responsible to develop, maintain and monitor the data platform infrastructure and operations. The infrastructure and pipelines you build will support data processing, data analytics, data science and data management across the CACI business. The data platform infrastructure will conform to a zero trust, least privilege architecture, with a strict adherence to data and infrastructure governance and control in a multi-account, multi-region AWS environment. You will use Infrastructure as Code and CI/CD to continuously improve, evolve and repair the platform. You will be able to design architectures and create re-useable solutions to reflect the business needs. Responsibilities Will Include Collaborating across CACI departments to develop and maintain the data platform Building infrastructure and data architectures in Cloud Formation, and SAM. Designing and implementing data processing environments and integrations using AWS PaaS such as Glue, EMR, Sagemaker, Redshift, Aurora and Snowflake Building data processing and analytics pipelines as code, using python, SQL, PySpark, spark, CloudFormation, lambda, step functions, Apache Airflow Monitoring and reporting on the data platform performance, usage and security Designing and applying security and access control architectures to secure sensitive data You Will Have 3+ years of experience in a Data Engineering role. Strong experience and knowledge of data architectures implemented in AWS using native AWS services such as S3, DataZone, Glue, EMR, Sagemaker, Aurora and Redshift. Experience administrating databases and data platforms Good coding discipline in terms of style, structure, versioning, documentation and unit tests Strong proficiency in Cloud Formation, Python and SQL Knowledge and experience of relational databases such as Postgres, Redshift Experience using Git for code versioning, and lifecycle management Experience operating to Agile principles and ceremonies Hands-on experience with CI/CD tools such as GitLab Strong problem-solving skills and ability to work independently or in a team environment. Excellent communication and collaboration skills. A keen eye for detail, and a passion for accuracy and correctness in numbers Whilst not essential, the following skills would also be useful: Experience using Jira, or other agile project management and issue tracking software Experience with Snowflake Experience with Spatial Data Processing More About The Opportunity The Data Engineer is an excellent opportunity, and CACI Services India reward their staff well with a competitive salary and impressive benefits package which includes: Learning: Budget for conferences, training courses and other materials Health Benefits: Family plan with 4 children and parents covered Future You: Matched pension and health care package We understand the importance of getting to know your colleagues. Company meetings are held every quarter, and a training/work brief weekend is held once a year, amongst many other social events. CACI is an equal opportunities employer. Therefore, we embrace diversity and are committed to a working environment where no one will be treated less favourably on the grounds of their sex, race, disability, sexual orientation religion, belief or age. We have a Diversity & Inclusion Steering Group and we always welcome new people with fresh perspectives from any background to join the group An inclusive and equitable environment enables us to draw on expertise and unique experiences and bring out the best in each other. We champion diversity, inclusion and wellbeing and we are supportive of Veterans and people from a military background. We believe that by embracing diverse experiences and backgrounds, we can collaborate to create better outcomes for our people, our customers and our society. Other details Pay Type Salary Apply Now Show more Show less

Job Title: GenAI Engineer Category: Software Development Required Experience: 3-4 years Location: Pune Job Description: As the Data Scientist, you will play a pivotal role in driving data-driven decision-making and advancing our organization's AI and analytical capabilities. You will lead a team of data scientists, collaborate with cross-functional teams, and contribute to the development and implementation of AI and advanced analytics solutions. This position requires a strong combination of technical expertise, leadership skills, and business acumen. Responsibilities: Team Leadership: ● Lead, mentor, and inspire a team of junior data scientists, fostering a collaborative and innovative work environment. ● Provide technical guidance, set priorities, and ensure the team's alignment with organizational goals. ● Conduct regular performance assessments and contribute to professional development plans. Strategy and Planning: ● Collaborate with stakeholders to understand business objectives and identify opportunities for leveraging data to achieve strategic goals. ● Develop and execute a data science roadmap, ensuring alignment with overall business and technology strategies. ● Stay abreast of industry trends, emerging technologies, and best practices in data science. Advanced Analytics: ● Design, develop, and implement advanced machine learning models and algorithms to extract insights and solve complex business problems. ● Drive the exploration and application of new data sources, tools, and techniques to enhance analytical capabilities. ● Collaborate with data engineers to ensure the scalability and efficiency of deployed models. Cross-functional Collaboration: ● Collaborate with cross-functional teams, including business analysts, software engineers, and domain experts, to integrate data science solutions into business processes. ● Communicate complex analytical findings to non-technical stakeholders in a clear and actionable manner. Data Governance and Quality: ● Establish and enforce data governance standards to ensure the accuracy, reliability, and security of data used for analysis. ● Work with data engineering teams to enhance data quality and integrity throughout the data lifecycle. Project Management: ● Oversee the end-to-end execution of data science projects, ensuring timelines, budgets, and deliverables are met. ● Provide regular project updates to stakeholders and manage expectations effectively. Technical Expertise: ● Provide technical guidance and execution for the latest GenAI technologies, including but not limited to LLM/SLM/VLM and Multi-modal AI Algorithms. Leverage Transformers for complex natural language processing-based tasks. ● Hands-on experience in RAG (Retrieval-Augmented Generation) pipelines using Pinecone or similar vector databases to enhance LLM performance. ● Experience building RESTful APIs and ML endpoints using FastAPI , integrating seamlessly with production systems. ● Apply LangChain and agentic frameworks to integrate LLMs with tools, memory, and reasoning chains. ● Proficiency in designing LLM-driven workflows , including prompt engineering , chain-of-thought reasoning, and OpenAI API call optimization to reduce latency and cost. ● Develop scalable event-driven architectures using AWS EventBridge , RDS , and other AWS services (e.g., S3, Glue, SageMaker). ● Develop and optimize embedding generation , storage, and retrieval processes using tools like OpenAI Embeddings, LangChain , and Pinecone. ● Lead the development of deep learning technologies like computer vision for image processing, OCR/IDP, object detection and tracking, segmentation, Image generation, Convolutional Neural Networks, Capsule Networks, etc. ● Development of core Machine Learning algorithms like time series analysis with Neural ODEs; Variational Autoencoders for Image Generation and anomaly detection; ● Provide oversight for core deep learning algorithms like Neural Architecture Search for optimization and Graph Neural Networks for molecular structures. Qualifications: ● Minimum 1+ years of experience leading a team of junior data scientists, with a proven track record of successful project implementations. ● Master's or Ph.D. in a quantitative field (Computer Science, Statistics, Mathematics, etc.) ● Experience with GenAI, Agentic AI, LLM Training, and LLM-driven workflow development. Knowledge of large multi-modal models is a must. ● Experience in MLOps, Scientific Machine Learning, Statistical Modeling, and Data Visualization. ● Proficiency in cloud platforms , particularly AWS (SageMaker, S3, RDS, EventBridge, Glue, Redshift). ● Must have experience with the development and implementation of various core Machine Learning algorithms mentioned above. ● Bonus: Prior experience in LLM observability, latency tuning, token usage monitoring, and fine-grained control of OpenAI or similar API integrations. ● Must have hands-on experience with Deep Learning technologies for computer vision and image processing as well as core neural network applications like optimization. ● Experience in developing ML, AI, and Data Science solutions and putting solutions in production, with proficiency in Data Engineering, is desirable. ● Experience in the development and implementation of scalable and efficient data pipelines using AWS services such as SageMaker, S3, Glue, and/or Redshift. ● Excellent leadership, communication, and interpersonal skills. ● Experience with big data technologies and cloud platforms is a plus. 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Make an impact with NTT DATA Join a company that is pushing the boundaries of what is possible. We are renowned for our technical excellence and leading innovations, and for making a difference to our clients and society. Our workplace embraces diversity and inclusion – it’s a place where you can grow, belong and thrive. Your day at NTT DATA Cloud AI/GenAI Engineer(ServiceNow) We are seeking a talented AI/GenAI Engineer to join our team in delivering cutting-edge AI solutions to clients. The successful candidate will be responsible for implementing, developing, and deploying AI/GenAI models and solutions on cloud platforms. This role requires knowledge of ServiceNow modules like CSM and virtual agent development. Candidate should have strong technical aptitude, problem-solving skills, and the ability to work effectively with clients and internal teams. What You'll Be Doing Key Responsibilities: Cloud AI Implementation: Implement and deploy AI/GenAI models and solutions using various cloud platforms (e.g., AWS SageMaker, Azure ML, Google Vertex AI) and frameworks (e.g., TensorFlow, PyTorch, LangChain, Vellum). Build Virtual Agent in SN – Design, develop and deploy virtual agents using SN agent builder Integrate SN – Design and develop seamless integration of SN with other external AI systems Agentic AI: Assist in developing agentic AI systems on cloud platforms, enabling autonomous decision-making and action-taking capabilities in AI solutions. Cloud-Based Vector Databases: Implement cloud-native vector databases (e.g., Pinecone, Weaviate, Milvus) or cloud-managed services for efficient similarity search and retrieval in AI applications. Model Evaluation and Fine-tuning: Evaluate and optimize cloud-deployed generative models using metrics like perplexity, BLEU score, and ROUGE score, and fine-tune models using techniques like prompt engineering, instruction tuning, and transfer learning. Security for Cloud LLMs: Apply security practices for cloud-based LLMs, including data encryption, IAM policies, and network security configurations. Client Support: Support client engagements by implementing AI requirements and contributing to solution delivery. Cloud Solution Implementation: Build scalable and efficient cloud-based AI/GenAI solutions according to architectural guidelines. Cloud Model Development: Develop and fine-tune AI/GenAI models using cloud services for specific use cases, such as natural language processing, computer vision, or predictive analytics. Testing and Validation: Conduct testing and validation of cloud-deployed AI/GenAI models, including performance evaluation and bias detection. Deployment and Maintenance: Deploy AI/GenAI models in production environments, ensuring seamless integration with existing systems and infrastructure. Cloud Deployment: Deploy AI/GenAI models in cloud production environments and integrate with existing systems. Requirements: Education: Bachelor/Master's in Computer Science, AI, ML, or related fields. Experience: 3-5 years of experience in engineering solutions, with a track record of delivering Cloud AI solutions. . Should have at least 2 years’ experience of SN and SN agent builder Technical Skills: Proficiency in cloud AI/GenAI services and technologies across major cloud providers (AWS, Azure, GCP) Experience with cloud-native vector databases and managed similarity search services Experience with SN modules like CSM and virtual agent builder Experience with security measures for cloud-based LLMs, including data encryption, access controls, and compliance requirements Programming Skills: Strong programming skills in languages like Python or R Cloud Platform Knowledge: Strong understanding of cloud platforms, their AI services, and best practices for deploying ML models in the cloud Communication: Excellent communication and interpersonal skills, with the ability to work effectively with clients and internal teams. Problem-Solving: Strong problem-solving skills, with the ability to analyse complex problems and develop creative solutions. Nice to have: Experience with serverless architectures for AI workloads Nice to have: Experience with ReactJS for rapid prototyping of cloud AI solution frontends Location: Delhi or Bangalore (with remote work options) Workplace type: Hybrid Working About NTT DATA NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long-term success. We invest over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure, and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group and headquartered in Tokyo. Equal Opportunity Employer NTT DATA is proud to be an Equal Opportunity Employer with a global culture that embraces diversity. We are committed to providing an environment free of unfair discrimination and harassment. We do not discriminate based on age, race, colour, gender, sexual orientation, religion, nationality, disability, pregnancy, marital status, veteran status, or any other protected category. Join our growing global team and accelerate your career with us. Apply today. Show more Show less