1628 Keras Jobs - Page 19

Building on our past. Ready for the future Worley is a global professional services company of energy, chemicals and resources experts. We partner with customers to deliver projects and create value over the life of their assets. We’re bridging two worlds, moving towards more sustainable energy sources, while helping to provide the energy, chemicals and resources needed now. The Role As a Data Science Lead with Worley, you will work closely with our existing team to deliver projects for our clients while continuing to develop your skills and experience etc…. Conceptualise, build and manage AI/ML (more focus on unstructured data) platform by evaluating and selecting best in industry AI/ML tools and frameworks Drive and take ownership for developing cognitive solutions for internal stakeholders & external customers. Conduct research in various areas like Explainable AI, Image Segmentation,3D object detections and Statistical Methods Evaluate not only algorithms & models but also available tools & technologies in the market to maximize organizational spend. Utilize the existing frameworks, standards, patterns to create architectural foundation and services necessary for AI/ML applications that scale from multi-user to enterprise class. Analyse marketplace trends - economical, social, cultural and technological - to identify opportunities and create value propositions. Offer a global perspective in stakeholder discussions and when shaping solutions/recommendations Analyse marketplace trends - economical, social, cultural and technological - to identify opportunities and create value propositions. Offer a global perspective in stakeholder discussions and when shaping solutions/recommendations IT Skills & Experience Thorough understanding of complete AI/ML project life cycle to establish processes & provide guidance & expert support to the team. Expert knowledge of emerging technologies in Deep Learning and Reinforcement Learning Knowledge of MLOps process for efficient management of the AI/ML projects. Must have lead project execution with other data scientists/ engineers for large and complex data sets Understanding of machine learning algorithms, such as k-NN, GBM, Neural Networks Naive Bayes, SVM, and Decision Forests. Experience in the AI/ML components like Jupyter Hub, Zeppelin Notebook, Azure ML studio, Spark ML lib, TensorFlow, Tensor flow,Keras, Py-Torch and Sci-Kit Learn etc Strong knowledge of deep learning with special focus on CNN/R-CNN/LSTM/Encoder/Transformer architecture Hands-on experience with large networks like Inseption-Resnets,ResNeXT-50. Demonstrated capability using RNNS for text, speech data, generative models Working knowledge of NoSQL (GraphX/Neo4J), Document, Columnar and In-Memory database models Working knowledge of ETL tools and techniques, such as Talend,SAP BI Platform/SSIS or MapReduce etc. Experience in building KPI /storytelling dashboards on visualization tools like Tableau/Zoom data People Skills Professional and open communication to all internal and external interfaces. Ability to communicate clearly and concisely and a flexible mindset to handle a quickly changing culture Strong analytical skills. Industry Specific Experience 10 -18 Years of experience of AI/ML project execution and AI/ML research Education – Qualifications, Accreditation, Training Master or Doctroate degree Computer Science Engineering/Information Technology /Artificial Intelligence Moving forward together We’re committed to building a diverse, inclusive and respectful workplace where everyone feels they belong, can bring themselves, and are heard. We provide equal employment opportunities to all qualified applicants and employees without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by law. We want our people to be energized and empowered to drive sustainable impact. So, our focus is on a values-inspired culture that unlocks brilliance through belonging, connection and innovation. And we're not just talking about it; we're doing it. We're reskilling our people, leveraging transferable skills, and supporting the transition of our workforce to become experts in today's low carbon energy infrastructure and technology. Whatever your ambition, there’s a path for you here. And there’s no barrier to your potential career success. Join us to broaden your horizons, explore diverse opportunities, and be part of delivering sustainable change. Company Worley Primary Location IND-MM-Navi Mumbai Other Locations IND-KR-Bangalore, IND-MM-Mumbai, IND-MM-Pune, IND-TN-Chennai, IND-GJ-Vadodara, IND-AP-Hyderabad, IND-WB-Kolkata Job Digital Platforms & Data Science Schedule Full-time Employment Type Employee Job Level Experienced Job Posting Jul 4, 2025 Unposting Date Aug 3, 2025 Reporting Manager Title Head of Data Intelligence

Job Description We're seeking top talents for our AI engineering team to develop high-quality machine learning models, services, and scalable data processing pipelines. Candidates should have a strong computer science background and be ready to handle end-to-end projects, focusing on engineering. As an Applied AI ML Lead within the Digital Intelligence team at JPMorgan, collaborate with all lines of business and functions to deliver software solutions. Experiment, develop, and productionize high-quality machine learning models, services, and platforms to make a significant impact on technology and business. Design and implement highly scalable and reliable data processing pipelines. Perform analysis and insights to promote and optimize business results. Contribute to a transformative journey and make a substantial impact on a wide range of customer products. Job Responsibilities Research, develop, and implement machine learning algorithms to solve complex problems related to personalized financial services in retail and digital banking domains. Work closely with cross-functional teams to translate business requirements into technical solutions and drive innovation in banking products and services. Collaborate with product managers, key business stakeholders, engineering, and platform partners to lead challenging projects that deliver cutting-edge machine learning-driven digital solutions. Conduct research to develop state-of-the-art machine learning algorithms and models tailored to financial applications in personalization and recommendation spaces. Design experiments, establish mathematical intuitions, implement algorithms, execute test cases, validate results, and productionize highly performant, scalable, trustworthy, and often explainable solutions. Collaborate with data engineers and product analysts to preprocess and analyze large datasets from multiple sources. Stay up-to-date with the latest publications in relevant Machine Learning domains and find applications for the same in your problem spaces for improved outcomes. Communicate findings and insights to stakeholders through presentations, reports, and visualizations. Work with regulatory and compliance teams to ensure that machine learning models adhere to standards and regulations. Mentor Junior Machine Learning associates in delivering successful projects and building successful careers in the firm. Participate and contribute back to firm-wide Machine Learning communities through patenting, publications, and speaking engagements. Required Qualifications, Capabilities And Skills Expert in at least one of the following areas: Natural Language Processing, Knowledge Graph, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis. Deep knowledge in Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics. Demonstrated expertise in machine learning frameworks: Tensorflow, Pytorch, pyG, Keras, MXNet, Scikit-Learn. Strong programming knowledge of python, spark; Strong grasp on vector operations using numpy, scipy; Strong grasp on distributed computation using Multithreading, Multi GPUs, Dask, Ray, Polars etc. Strong analytical and critical thinking skills for problem solving. Excellent written and oral communication along with demonstrated teamwork skills. Demonstrated ability to clearly communicate complex technical concepts to both technical and non-technical audiences Experience in working in interdisciplinary teams and collaborating with other researchers, engineers, and stakeholders. A strong desire to stay updated with the latest advancements in the field and continuously improve one's skills Preferred Qualification, Capabilities And Skills Deep hands-on experience with real-world ML projects, either through academic research, internships, or industry roles. Experience with distributed data/feature engineering using popular cloud services like AWS EMR Experience with large scale training, validation and testing experiments. Experience with cloud Machine Learning services in AWS like Sagemaker. Experience with Container technology like Docker, ECS etc. Experience with Kubernetes based platform for Training or Inferencing. Contributions to open-source ML projects can be a plus. Participation in ML competitions (e.g., Kaggle) and hackathons demonstrating practical skills and problem-solving abilities. Understanding of how ML can be applied to various domains like healthcare, finance, robotics, etc. ABOUT US

Job Description We're seeking top talents for our AI engineering team to develop high-quality machine learning models, services, and scalable data processing pipelines. Candidates should have a strong computer science background and be ready to handle end-to-end projects, focusing on engineering. As an Applied AI ML Senior Associate within the Digital Intelligence team at JPMorgan, collaborate with all lines of business and functions to deliver software solutions. Experiment, develop, and productionize high-quality machine learning models, services, and platforms to make a significant impact on technology and business. Design and implement highly scalable and reliable data processing pipelines. Perform analysis and insights to promote and optimize business results. Contribute to a transformative journey and make a substantial impact on a wide range of customer products. Job Responsibilities Research, develop, and implement machine learning algorithms to solve complex problems related to personalized financial services in retail and digital banking domains. Work closely with cross-functional teams to translate business requirements into technical solutions and drive innovation in banking products and services. Collaborate with product managers, key business stakeholders, engineering, and platform partners to lead challenging projects that deliver cutting-edge machine learning-driven digital solutions. Conduct research to develop state-of-the-art machine learning algorithms and models tailored to financial applications in personalization and recommendation spaces. Design experiments, establish mathematical intuitions, implement algorithms, execute test cases, validate results, and productionize highly performant, scalable, trustworthy, and often explainable solutions. Collaborate with data engineers and product analysts to preprocess and analyze large datasets from multiple sources. Stay up-to-date with the latest publications in relevant Machine Learning domains and find applications for the same in your problem spaces for improved outcomes. Communicate findings and insights to stakeholders through presentations, reports, and visualizations. Work with regulatory and compliance teams to ensure that machine learning models adhere to standards and regulations. Mentor Junior Machine Learning associates in delivering successful projects and building successful careers in the firm. Participate and contribute back to firm-wide Machine Learning communities through patenting, publications, and speaking engagements. Required Qualifications, Capabilities And Skills Expert in at least one of the following areas: Natural Language Processing, Knowledge Graph, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis. Deep knowledge in Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics. Demonstrated expertise in machine learning frameworks: Tensorflow, Pytorch, pyG, Keras, MXNet, Scikit-Learn. Strong programming knowledge of python, spark; Strong grasp on vector operations using numpy, scipy; Strong grasp on distributed computation using Multithreading, Multi GPUs, Dask, Ray, Polars etc. Strong analytical and critical thinking skills for problem solving. Excellent written and oral communication along with demonstrated teamwork skills. Demonstrated ability to clearly communicate complex technical concepts to both technical and non-technical audiences Experience in working in interdisciplinary teams and collaborating with other researchers, engineers, and stakeholders. A strong desire to stay updated with the latest advancements in the field and continuously improve one's skills Preferred Qualification, Capabilities And Skills Deep hands-on experience with real-world ML projects, either through academic research, internships, or industry roles. Experience with distributed data/feature engineering using popular cloud services like AWS EMR Experience with large scale training, validation and testing experiments. Experience with cloud Machine Learning services in AWS like Sagemaker. Experience with Container technology like Docker, ECS etc. Experience with Kubernetes based platform for Training or Inferencing. Contributions to open-source ML projects can be a plus. Participation in ML competitions (e.g., Kaggle) and hackathons demonstrating practical skills and problem-solving abilities. Understanding of how ML can be applied to various domains like healthcare, finance, robotics, etc. ABOUT US

Scale an existing RAG code base for a production grade AI application Proficiency in Prompt Engineering, LLMs, and Retrieval Augmented Generation Programming languages like Python or Java Experience with vector databases Experience using LLMs in software applications, including prompting, calling, and processing outputs Experience with AI frameworks such as LangChain Troubleshooting skills and creative in finding new ways to leverage LLM Experience with Azure Proof of Concept (POC) DevelopmentDevelop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another, particularly COBOL to JAVA through rapid prototypes/ PoC Documentation and Knowledge SharingDocument solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides. Contribute to internal knowledge sharing initiatives and mentor new team members. Industry Trends and InnovationStay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation. Experience in python and pyspark will be added advantage Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g. Kubernetes, AWS, Azure, GCP) and related services is a plus. Experience and working knowledge in COBOL & JAVA would be preferred Having experience in Code generation, code matching & code translation Prepare the effort estimates, WBS, staffing plan, RACI, RAID etc. . Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI. Demonstrate a growth mindset to understand clients' business processes and challenges Preferred technical and professional experience EducationBachelor's, Master's, or Ph.D. degree in Computer Science, Artificial Intelligence, Data Science or a related field. Ability to communicate with internal and external clients to understand and define business needs, providing analytical solutions Ability to communicate results to technical and non-technical audiences

As an Associate Data Scientist at IBM, you will work to solve business problems using leading edge and open-source tools such as Python, R, and TensorFlow, combined with IBM tools and our AI application suites. You will prepare, analyze, and understand data to deliver insight, predict emerging trends, and provide recommendations to stakeholders. In your role, you may be responsible for: Implementing and validating predictive and prescriptive models and creating and maintaining statistical models with a focus on big data & incorporating machine learning. techniques in your projects Writing programs to cleanse and integrate data in an efficient and reusable manner Working in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviors Communicating with internal and external clients to understand and define business needs and appropriate modelling techniques to provide analytical solutions. Evaluating modelling results and communicating the results to technical and non-technical audiences. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Proof of Concept (POC) DevelopmentDevelop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another, particularly COBOL to JAVA through rapid prototypes/ PoC Document solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides Preferred technical and professional experience Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms Experience and working knowledge in COBOL & JAVA would be preferred Experience in python and pyspark will be added advantage

Your role Location: Chennai Work Hours: 12 PM – 9 PM IST Work Mode: Onsite – 5 days a week We are looking for a detail-oriented and proactive Senior Data Scientist for our Cross-Border line of business. In this pivotal role, you will work closely with the North America Quantitative Analytics leadership team to deliver high-impact data analysis and reporting in support of our Credit and Treasury functions. You will play a hands-on role in maintaining and enhancing our core reporting infrastructure, performing critical data analysis, and supporting operational excellence across our analytics efforts. This role is ideal for an experienced analyst ready to take ownership of high-impact deliverables and collaborate across global teams. What you'll be doing Own and deliver complex, business-as-usual (BAU) reports. Analyze large datasets to extract insights, trends, and identify improvement opportunities. Collaborate with North American stakeholders to gather requirements and deliver data-driven solutions. Utilize SQL, Python, and Excel for data extraction, transformation, and reporting automation. Work with internal partners to resolve data issues and ensure accuracy. Proactively troubleshoot anomalies and communicate findings and resolutions. Support data integration from new sources and adapt to evolving reporting needs. Contribute to continuous improvements in reporting efficiency, accuracy, and control measures. 5–7 years of experience in data analysis, business intelligence, or a related role. Bachelor’s or Master’s degree in Computer Science, Mathematics, Engineering, Statistics, or a related field. Proficiency in SQL, Python, and Excel . Working knowledge of VBA, data visualization, or AI tools is a plus. Strong attention to detail and data quality. Eagerness to learn about compliance and risk in a data context. Ability to work independently, manage deadlines, and collaborate effectively. Experience working with global stakeholders. Familiarity with financial services is preferred but not required. Willingness to work in office, during the specified shift hours, is mandatory . About Corpay Corpay is a global technology organisation that is leading the future of commercial payments with a culture of innovation that drives us to constantly create new and better ways to pay. Our specialized payment solutions help businesses control, simplify, and secure payment for fuel, general payables, toll and lodging expenses. Millions of people in over 80 countries around the world use our solutions for their payments. All offers of employment made by Corpay (and its subsidiary companies) are subject to the successful completion of satisfactory pre-employment vetting by an independent supplier (Experian). This is in accordance with Corpay's Resourcing Policy and include employment referencing, identity, adverse financial, criminal and sanctions list checks. We do this to meet our legal and regulatory requirements. Corpay is dedicated to encouraging a supportive and inclusive culture among our employees. It is within our best interest to promote diversity and eliminate discrimination in the workplace. We seek to ensure that all employees and job applicants are given equal opportunities. Notice to Agency and Search Firm Representatives: Corpay will not accept unsolicited CV's from agencies and/or search firms for this job posting. Resumes submitted to any Corpay employee by a third party agency and/or search firm without a valid written & signed search agreement, will become the sole property of Corpay. No fee will be paid if a candidate is hired for this position as a result of an unsolicited agency or search firm referral. Thank you.

All Positions Data Science Engineer Noida | 2 - 4 years Apply Now Welcome to BUSINESSNEXT, where we believe in maximizing your true potential while doing something purposeful. Our commitment to innovation and forward-thinking is reflected in everything we do, and we're looking for like-minded individuals to join our team. If you're looking for a rewarding career in a company that values your creativity, we invite you to explore this opportunity. The Opportunity We are looking for a highly skilled and technically proficient Sr Engineer with 3-5 years of experience to lead our AI initiatives, with a specific focus on Generative AI, Natural Language Processing (NLP), and Machine Learning (ML). The ideal candidate should have hands-on experience in delivering and commercializing AI solutions, with deep expertise in Generative AI technologies and frameworks. An understanding of computer vision is a plus. This role requires both technical depth and leadership skills to drive AI innovation and deploy production-grade AI models. Objectives Aligned To This Role Fostering inventive concepts and effectively implementing strategic initiatives to attain significant outcomes in the realm of product development. Join our team of Engineers and be a part of our reforming BusinessNext Platform. Within this realm of cutting-edge technology, you'll play a pivotal role in shaping the future of digital innovation on a global scale. What would you do? Lead AI projects focused on Generative AI, NLP, and ML, ensuring successful deployment and commercialization of AI-driven solutions. Provide deep technical guidance and hands-on development expertise, specifically in Generative AI technologies (e.g., GANs, VAEs, Transformers). Design, build, and scale AI models across various domains, ensuring they meet business objectives and performance metrics. Collaborate with data scientists, machine learning engineers, and product teams to integrate AI models into production environments. Manage the end-to-end lifecycle of AI projects, from ideation, research, prototyping, and development to final product delivery and commercialization. Stay current with the latest advancements in Generative AI and NLP, and proactively apply emerging trends and technologies to ongoing projects. Lead and mentor a team of AI engineers, fostering innovation and a results-driven approach. Drive the development of robust AI pipelines and solutions that are scalable, efficient, and aligned with business goals. Present technical and non-technical stakeholders with project progress, key findings, and commercial strategies. Ensure AI models are developed with strong considerations for performance, accuracy, scalability, and ethical AI practices. Required Skills Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 3-5 years of experience in AI/ML, with in-depth expertise in Generative AI and NLP technologies. Hands-on experience with Generative AI techniques such as GANs, VAEs, diffusion models, large language models (LLMs), Transformers, Agentic frameworks. Proven track record of successfully commercializing multiple AI projects. Strong knowledge of ML algorithms, statistical models, and deep learning techniques. Experience in deploying AI models into production at scale, using cloud platforms like AWS, Azure, or GCP. Proficiency in AI/ML frameworks and tools such as TensorFlow, PyTorch, Keras, and Hugging Face. Good understanding of Computer Vision is a plus. Strong leadership and project management skills with the ability to manage multiple projects simultaneously. Ability to mentor and guide a technical team while also being hands-on with AI development tasks. Excellent problem-solving skills and a business-focused mindset for AI solution delivery. Educational Qualifications Engineering/ equivalent technical qualification from a reputed college/ university. Good understanding of current technology trends along with ultra-scalable systems. Proficient in effectively communicating with internal stakeholders across various domains, including technology and business. Meet The Team Connect with the team that loves the challenge of solving business problems, just like you! Ravi Kumar SVP - Datanext Why BusinessNext? WIIFM, you ask? 😊 Well, lots of real, get-your-hands-dirty gigs, building cool products for the BFSI industry that is rapidly digitizing. Expect a challenging work experience that you’re unlikely to get in a Services Company. Come, #Unlimit your true Potential today to be #UpForTomorrow We exist for growth and development: We’re a company that is built on a Coaching Culture, committed to supporting employees to reach their full potential, helping them achieve their professional goals while contributing to the Moonshot. We thrive on clear, lucid Objectives & Key Results (OKRs). A trusting, transparent relationship where an Individual’s OKRs, lock into the department’s which, in turn, lock into the Company’s! We thrive by being proactive: Our Brand tagline "Up For Tomorrow" implies being proactive and forward-thinking, and our Culture Philosophy of "Unlimit" speaks of having no limits on what one can achieve. You can expect a culture that will constantly encourage you to take initiative and be proactive in your career, taking charge of your own professional development. Caring for People is our Business, and a Values-led Culture is our Profit. We just happen to use tech in the process. We’re a bunch of friends with Benefits: Coaching Sessions, Training and development opportunities, flexible working hours, and remote work options are just some of the perks of this Culture. Designed around you the employee so you can take advantage of opportunities to grow and develop and be ready for the future. Some quick facts Ours is an inspiring Garage-to-Unicorn Product story that has been scripted by gifted technologists who’re just like you. We are among the fastest growing SaaS companies in India, especially in the BFSI industry, with a global footprint, serving over 1 million+ users across 50+ countries Our clientele is based out in Asia Pac, USA, Middle East, South Africa, Australia, etc. Our product engages millions of global users, and we keep adding millions every month We are on a mission We sure are - on an 8-year Moon-shot Mission to be specific. We want to accelerate the World’s transition to intuitive, digital, and joyful financial experiences and become a Decacorn in the process. Does this excite you, then join us! 😊 Apply Now

2+ years of ML + NLP experience. Programming in Python. Knowledge of SQL and NoSQL databases. Expert ability to write robust code in Python. Experience working with structured and unstructured data including data extraction, integration, and normalization. Very fluent in ML frameworks/libraries like Tensorflow, Pytorch, ONNX, Scikit Learn, Keras, Spacy. Expert skill at manipulating data frames using Pandas and arrays using NumPy. Good To Have Experience with big data frameworks such as Spark and Hadoop. Experience with containerizing applications using docker.

Senior AI/ML Engineer Primary Skills Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio Job requirements Key Responsibilities Develop and optimize machine learning models for various applications. Implement AI algorithms, including deep learning, neural networks, and natural language processing (NLP). Design and maintain data pipelines for model training and deployment. Collaborate with cross-functional teams to integrate AI solutions into products. Conduct research on emerging AI technologies and best practices. Ensure scalability, reliability, and efficiency of AI models in production environments. Troubleshoot and improve existing AI/ML systems. Required Skills & Qualifications - Experience: 3-8 years in AI/ML development. Technical Skills: Proficiency in Python, TensorFlow, PyTorch, and other ML frameworks. Data Handling: Strong knowledge of data preprocessing, feature engineering, and model evaluation. Cloud & Deployment: Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). Problem-Solving: Ability to analyze complex problems and develop AI-driven solutions.

Senior Data Science Lead Primary Skills Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio Job requirements JD is below: The Agentic AI Lead is a pivotal role responsible for driving the research, development, and deployment of semi-autonomous AI agents to solve complex enterprise challenges. This role involves hands-on experience with LangGraph, leading initiatives to build multi-agent AI systems that operate with greater autonomy, adaptability, and decision-making capabilities. The ideal candidate will have deep expertise in LLM orchestration, knowledge graphs, reinforcement learning (RLHF/RLAIF), and real-world AI applications. As a leader in this space, they will be responsible for designing, scaling, and optimizing agentic AI workflows, ensuring alignment with business objectives while pushing the boundaries of next-gen AI automation. ________________________________________ Key Responsibilities 1. Architecting & Scaling Agentic AI Solutions Design and develop multi-agent AI systems using LangGraph for workflow automation, complex decision-making, and autonomous problem-solving. Build memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains. Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications. 2. Hands-On Development & Optimization Develop and optimize agent orchestration workflows using LangGraph, ensuring high performance, modularity, and scalability. Implement knowledge graphs, vector databases (Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning. Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making. 3. Driving AI Innovation & Research Lead cutting-edge AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents. Stay ahead of advancements in multi-agent systems, AI planning, and goal-directed behavior, applying best practices to enterprise AI solutions. Prototype and experiment with self-learning AI agents, enabling autonomous adaptation based on real-time feedback loops. 4. AI Strategy & Business Impact Translate Agentic AI capabilities into enterprise solutions, driving automation, operational efficiency, and cost savings. Lead Agentic AI proof-of-concept (PoC) projects that demonstrate tangible business impact and scale successful prototypes into production. 5. Mentorship & Capability Building Lead and mentor a team of AI Engineers and Data Scientists, fostering deep technical expertise in LangGraph and multi-agent architectures. Establish best practices for model evaluation, responsible AI, and real-world deployment of autonomous AI agents. ________________________________________

Senior Data Science Lead Primary Skills Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio Job requirements JD is below: The Agentic AI Lead is a pivotal role responsible for driving the research, development, and deployment of semi-autonomous AI agents to solve complex enterprise challenges. This role involves hands-on experience with LangGraph, leading initiatives to build multi-agent AI systems that operate with greater autonomy, adaptability, and decision-making capabilities. The ideal candidate will have deep expertise in LLM orchestration, knowledge graphs, reinforcement learning (RLHF/RLAIF), and real-world AI applications. As a leader in this space, they will be responsible for designing, scaling, and optimizing agentic AI workflows, ensuring alignment with business objectives while pushing the boundaries of next-gen AI automation. ________________________________________ Key Responsibilities 1. Architecting & Scaling Agentic AI Solutions Design and develop multi-agent AI systems using LangGraph for workflow automation, complex decision-making, and autonomous problem-solving. Build memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains. Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications. 2. Hands-On Development & Optimization Develop and optimize agent orchestration workflows using LangGraph, ensuring high performance, modularity, and scalability. Implement knowledge graphs, vector databases (Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning. Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making. 3. Driving AI Innovation & Research Lead cutting-edge AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents. Stay ahead of advancements in multi-agent systems, AI planning, and goal-directed behavior, applying best practices to enterprise AI solutions. Prototype and experiment with self-learning AI agents, enabling autonomous adaptation based on real-time feedback loops. 4. AI Strategy & Business Impact Translate Agentic AI capabilities into enterprise solutions, driving automation, operational efficiency, and cost savings. Lead Agentic AI proof-of-concept (PoC) projects that demonstrate tangible business impact and scale successful prototypes into production. 5. Mentorship & Capability Building Lead and mentor a team of AI Engineers and Data Scientists, fostering deep technical expertise in LangGraph and multi-agent architectures. Establish best practices for model evaluation, responsible AI, and real-world deployment of autonomous AI agents. ________________________________________

• Develop strategies/solutions to solve problems in logical yet creative ways, leveraging state-of-the-art machine learning, deep learning and GEN AI techniques. • Technically lead a team of data scientists to produce project deliverables on time and with high quality. • Identify and address client needs in different domains, by analyzing large and complex data sets, processing, cleansing, and verifying the integrity of data, and performing exploratory data analysis (EDA) using state-of-the-art methods. • Select features, build and optimize classifiers/regressors, etc. using machine learning and deep learning techniques. • Enhance data collection procedures to include information that is relevant for building analytical systems, and ensure data quality and accuracy. • Perform ad-hoc analysis and present results in a clear manner to both technical and non-technical stakeholders. • Create custom reports and presentations with strong data visualization and storytelling skills to effectively communicate analytical conclusions to senior officials in a company and other stakeholders. • Expertise in data mining, EDA, feature selection, model building, and optimization using machine learning and deep learning techniques. • Strong programming skills in Python. • Excellent communication and interpersonal skills, with the ability to present complex analytical concepts to both technical and non-technical stakeholders. Primary Skills : - Excellent understanding and hand-on experience of data-science and machine learning techniques & algorithms for supervised & unsupervised problems, NLP and computer vision and GEN AI. Good applied statistics skills, such as distributions, statistical inference & testing, etc. - Excellent understanding and hand-on experience on building Deep-learning models for text & image analytics (such as ANNs, CNNs, LSTM, Transfer Learning, Encoder and decoder, etc). - Proficient in coding in common data science language & tools such as R, Python. - Experience with common data science toolkits, such as NumPy, Pandas, Matplotlib, StatsModel, Scikitlearn, SciPy, NLTK, Spacy, OpenCV etc. - Experience with common data science frameworks such as Tensorflow, Keras, PyTorch, XGBoost,etc. - Exposure or knowledge in cloud (Azure/AWS). - Experience on deployment of model in production.

JOB DESCRIPTION We're seeking top talents for our AI engineering team to develop high-quality machine learning models, services, and scalable data processing pipelines. Candidates should have a strong computer science background and be ready to handle end-to-end projects, focusing on engineering. As an Applied AI ML Lead within the Digital Intelligence team at JPMorgan, collaborate with all lines of business and functions to deliver software solutions. Experiment, develop, and productionize high-quality machine learning models, services, and platforms to make a significant impact on technology and business. Design and implement highly scalable and reliable data processing pipelines. Perform analysis and insights to promote and optimize business results. Contribute to a transformative journey and make a substantial impact on a wide range of customer products. Job Responsibilities Research, develop, and implement machine learning algorithms to solve complex problems related to personalized financial services in retail and digital banking domains. Work closely with cross-functional teams to translate business requirements into technical solutions and drive innovation in banking products and services. Collaborate with product managers, key business stakeholders, engineering, and platform partners to lead challenging projects that deliver cutting-edge machine learning-driven digital solutions. Conduct research to develop state-of-the-art machine learning algorithms and models tailored to financial applications in personalization and recommendation spaces. Design experiments, establish mathematical intuitions, implement algorithms, execute test cases, validate results, and productionize highly performant, scalable, trustworthy, and often explainable solutions. Collaborate with data engineers and product analysts to preprocess and analyze large datasets from multiple sources. Stay up-to-date with the latest publications in relevant Machine Learning domains and find applications for the same in your problem spaces for improved outcomes. Communicate findings and insights to stakeholders through presentations, reports, and visualizations. Work with regulatory and compliance teams to ensure that machine learning models adhere to standards and regulations. Mentor Junior Machine Learning associates in delivering successful projects and building successful careers in the firm. Participate and contribute back to firm-wide Machine Learning communities through patenting, publications, and speaking engagements. Required qualifications, capabilities and skills Expert in at least one of the following areas: Natural Language Processing, Knowledge Graph, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis. Deep knowledge in Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics. Demonstrated expertise in machine learning frameworks: Tensorflow, Pytorch, pyG, Keras, MXNet, Scikit-Learn. Strong programming knowledge of python, spark; Strong grasp on vector operations using numpy, scipy; Strong grasp on distributed computation using Multithreading, Multi GPUs, Dask, Ray, Polars etc. Strong analytical and critical thinking skills for problem solving. Excellent written and oral communication along with demonstrated teamwork skills. Demonstrated ability to clearly communicate complex technical concepts to both technical and non-technical audiences Experience in working in interdisciplinary teams and collaborating with other researchers, engineers, and stakeholders. A strong desire to stay updated with the latest advancements in the field and continuously improve one's skills Preferred qualification, capabilities and skills Deep hands-on experience with real-world ML projects, either through academic research, internships, or industry roles. Experience with distributed data/feature engineering using popular cloud services like AWS EMR Experience with large scale training, validation and testing experiments. Experience with cloud Machine Learning services in AWS like Sagemaker. Experience with Container technology like Docker, ECS etc. Experience with Kubernetes based platform for Training or Inferencing. Contributions to open-source ML projects can be a plus. Participation in ML competitions (e.g., Kaggle) and hackathons demonstrating practical skills and problem-solving abilities. Understanding of how ML can be applied to various domains like healthcare, finance, robotics, etc. ABOUT US

Design, develop, and maintain digital pathology and medical imaging software solutions, adhering to DICOM and related standards. Integrate and optimize AI/machine learning models within imaging workflows for tasks such as classification, segmentation, or feature extraction. Collaborate with cross-functional teams, including data scientists, clinicians, and product managers, to gather requirements and deliver high-quality solutions. Develop and support robust pipelines for image data ingestion, secure storage, retrieval, visualization, and analysis. Work with large-scale clinical and research imaging datasets, ensuring data integrity, compliance, and performance. Utilize and extend industry-standard imaging libraries and toolkits such as pydicom, OpenSlide, and ITK. Implement and maintain comprehensive software documentation, tests, and quality assurance processes. Participate in peer code reviews to ensure coding standards and best practices. Stay current with industry trends, new standards such as DICOMweb, and emerging technologies in digital pathology and AI. Contribute to the continuous improvement of engineering processes, including CI/CD pipelines and containerization strategies. Support troubleshooting, debugging, and resolution of image data and software-related issues. Ensure compliance with healthcare regulations and standards regarding data security and software quality. Mandatory Skills: Strong programming proficiency in Python. Solid understanding of DICOM and/or digital pathology standards such as WSI, DICOMweb, and HL7. Experience with medical imaging libraries or toolkits such as pydicom and OpenSlide. In-depth knowledge of AWS services, including but not limited to EC2, S3, Lambda, RDS, IAM, CloudFormation, and API Gateway. Familiarity with database technologies, whether SQL or NoSQL, for imaging data management. Experience working with large-scale image datasets, including secure storage and efficient retrieval. Understanding of version control systems such as Git. Strong skills in technical documentation and producing maintainable code. Ability to work effectively in a collaborative, multidisciplinary team environment. Excellent written and verbal communication skills. Preferred Skills: Experience developing, integrating, or deploying AI/machine learning models for medical imaging tasks such as image classification, segmentation, or feature extraction. Familiarity with deep learning frameworks such as TensorFlow, PyTorch, or Keras. Knowledge of annotation tools and data formats commonly used in pathology and imaging datasets. Experience with containerization technologies such as Docker and Kubernetes, along with cloud engineering practices. Understanding of continuous integration/continuous deployment (CI/CD) pipelines and automated testing frameworks. Prior work on whole slide imaging (WSI) workflows and digital pathology image viewers. Educational Requirements: Bachelors or masters degree in computer science or an IT-related discipline with at least 8 years of experience in the IT industry.

A Computer Science Degree (Bachelors or Masters), Mathematics or Statistics (Masters) Total of 8-12 years of Big Data, Business Intelligence, Data warehousing, Artificial Intelligence and Machine Learning experience At least 2 years of experience in data science in rolling out production grade solutions to end customers Technical Skills: Experience in designing and deploying Analytical Systems, End to end. Excellent problem-solving skills Strong verbal and written communication skills Strong hands-on programming experience with R or Python or Java Hands-on experience with any of the data science platforms such as RapidMiner, SAS and IBM Sound understanding of machine learning algorithms, including classification, clustering, association and recommendation generation Familiarity with Open Source Machine Learning (R, Python), NLP toolkits and deep learning frameworks (TensorFlow, Keras, H2O etc.) Working experience with statistical inference Experience with BI (Tableau, Oracle, IBM, Microsoft), Data Science (RapidMiner/ SAS/ IBM), NoSQL (MongoDB, Cassandra, Hadoop, Spark), RDBMS (Oracle, SQL Server) tools Experience using cloud computing and storage frameworks such as Amazon AWS (EC2, S3, Redshift, RDS) and Microsoft Azure Storage

A Computer Science Degree (Bachelors or Masters), Mathematics or Statistics (Masters) Total of 3-5 years of Big Data, Business Intelligence, Data warehousing, Artificial Intelligence and Machine Learning experience At least 2 years of experience in data science in rolling out production grade solutions to end customers Technical Skills: Experience in designing and deploying Analytical Systems, End to end. Excellent problem-solving skills Strong verbal and written communication skills Strong hands-on programming experience with R or Python or Java Hands-on experience with any of the data science platforms such as Rapid Miner, Spark,SAS and IBM Sound understanding of machine learning algorithms, including classification, clustering, association and recommendation generation Familiarity with Open Source Machine Learning (R, Python), NLP toolkits and deep learning frameworks (TensorFlow, Keras, H2O etc.) Working experience with statistical inference Experience with BI (Tableau, Oracle, IBM, Microsoft), Data Science (RapidMiner/ SAS/ IBM), NoSQL (MongoDB, Cassandra, Hadoop, Spark), RDBMS (Oracle, SQL Server) tools Experience using cloud computing and storage frameworks such as Amazon AWS (EC2, S3, Redshift, RDS) and Microsoft Azure Storage

Role: Gen AI Engineer Location: Hyderabad Experience: 5+ years Mode of Interview: Scheduled in-person interview only Date: 12th July Job Description: Collect and prepare data for training and evaluating multimodal foundation models. This may involve cleaning and processing text data or creating synthetic data. Develop and optimize large-scale language models like GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders) Work on tasks involving language modeling, text generation, understanding, and contextual comprehension. Regularly review and fine-tune Large Language models to ensure maximum accuracy and relevance for custom datasets. Build and deploy AI applications on cloud platforms – any hyperscaler Azure, GCP or AWS. Integrate AI models with our company's data to enhance and augment existing applications. Role & Responsibility Handle data preprocessing, augmentation, and generation of synthetic data. Design and develop backend services using Python or .NET to support OpenAI-powered solutions (or any other LLM solution) Develop and Maintaining AI Pipelines Work with custom datasets, utilizing techniques like chunking and embeddings, to train and fine-tune models. Integrate Azure cognitive services (or equivalent platform services) to extend functionality and improve AI solutions Collaborate with cross-functional teams to ensure smooth deployment and integration of AI solutions. Ensure the robustness, efficiency, and scalability of AI systems. Stay updated with the latest advancements in AI and machine learning technologies. Skills & Experience Strong foundation in machine learning, deep learning, and computer science. Expertise in generative AI models and techniques (e.g., GANs, VAEs, Transformers). Experience with natural language processing (NLP) and computer vision is a plus. Ability to work independently and as part of a team. Knowledge of advanced programming like Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models. Knowledge of Natural language processing (NLP) for text generation projects like text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models. Experience in Data management, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models. Experience in developing and deploying AI models in production environments. Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying , managing and scaling AI solutions Should be able to bring new ideas and innovative solutions to our clients

Job Title: Python & AI Developer Location: Mohali 8B Experience: 2–7 Years Job Summary: We are seeking a skilled Python & AI Developer to join our team. The ideal candidate will have strong experience in Python programming and hands-on expertise in Artificial Intelligence and Machine Learning. You will be responsible for designing, developing, and deploying AI-based applications and solutions. Key Responsibilities: Develop and maintain AI/ML models using Python. Work with large datasets: cleaning, processing, and analyzing data. Build predictive and classification models using algorithms like Regression, Decision Trees, SVM, CNN, RNN, etc. Deploy AI solutions into production environments using Flask, FastAPI, or other frameworks. Collaborate with data scientists, analysts, and backend engineers to integrate models into existing systems. Write efficient, reusable, and testable code. Stay up to date with the latest AI and machine learning trends. Required Skills: Proficient in Python and AI/ML libraries such as TensorFlow, Keras, PyTorch, scikit-learn, NumPy, Pandas. Strong understanding of AI/ML algorithms, deep learning, and statistical modeling. Experience with data preprocessing and model evaluation techniques. Familiarity with RESTful APIs, Flask/Django/FastAPI for model deployment. Knowledge of cloud platforms (AWS, GCP, Azure) is a plus. Good problem-solving and communication skills. Preferred Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, or related field. Experience with version control systems (e.g., Git). Familiarity with NLP, computer vision, or reinforcement learning is a bonus. Job Types: Full-time, Permanent Schedule: Day shift Monday to Friday Work Location: In person

Job Title: AI Trainer (Project-Based / Freelance) Location: On-Site Job Type: Project-Based / Freelance Experience Required: 2+ years in AI/ML training or practical AI development Job Summary: We are seeking a skilled AI Trainer on a project basis to conduct hands-on training sessions for interns and new employees. The ideal candidate should have strong expertise in AI tools and the ability to explain AI/ML concepts clearly while providing practical training. Key Responsibilities: Deliver project-based training programs on AI/ML fundamentals and tools. Train interns and freshers on essential AI tools and frameworks including: Python and libraries like NumPy, Pandas, Scikit-learn, TensorFlow, Keras, PyTorch Jupyter Notebook / Google Colab for practical coding OpenAI tools (e.g., ChatGPT, API usage) NLP libraries such as spaCy, NLTK Data visualization tools like Matplotlib, Seaborn Version control using Git/GitHub Prepare training materials, hands-on assignments, and evaluations. Provide feedback and support to trainees during the training period. Update training content based on latest AI developments. Work remotely with flexible hours, delivering sessions according to project schedules. Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, AI or related field. Minimum 2 years’ experience in AI/ML development and/or training. Proven ability to train or mentor beginners in AI tools and technologies. Excellent communication and presentation skills. Self-motivated and able to manage training projects independently. Preferred: Experience with cloud AI platforms (AWS, GCP, Azure). Knowledge of Generative AI tools. Relevant certifications in AI/ML training. Job Types: Contractual / Temporary, Freelance Contract length: 3 months Pay: From ₹2,000.00 per month Schedule: Day shift Morning shift Supplemental Pay: Commission pay Language: English (Preferred) Work Location: In person

Job Role: ML Research Engineer - ASR (Automatic Speech Recognition) Experience : 2+ years of experience Location: Chennai, Tamil Nadu About the Company: Kaizen being a reputed company is involved in the business of Kaizen Secure Voiz Private Limited is Six-year young company specializing in unified voice interactions management using latest technologies with Global presence for Supply, implementation, testing and commissioning of voice biometrics solution. KSV has good experience in design, development and implementation of such voice biometrics- based technologies and has enabled multi-channel applications such as mobile applications, voice bots, interactive voice response and call center-based services to target group. KSV has proposed options to customers, keeping the world trend on latest technologies. KSV has deployed similar solutions for various companies and understands domain very well. While KSV has proposed voice biometrics-based Interactions management platform is suitable for further scaling and improvements of customer experience using voice analytics solutions later. The introduction of such automation will not only save huge money for the company, but also exponentially increase the customer experience. Responsibilities: Develop and implement Voice Biometric algorithms and models. Evaluate and analyze the performance of Voice Biometric systems. Implement advanced security measures to protect biometric data and ensure compliance with privacy regulations. Optimize the performance of biometric systems to ensure fast and accurate identification and authentication. Fine-tune algorithms and parameters to improve system efficiency and reliability. Collaborate with cross-functional teams to integrate Voice Biometric solutions into various applications and systems. Stay updated with the latest advancements in Voice Biometric technology and contribute to research activities. Impeccable analytical and problem-solving skills Extensive math and computer skills, with a deep understanding of probability, statistics, and algorithms In-depth knowledge of machine learning frameworks, like Keras, PyTorch, etc Familiarity with data structures, data modelling, and software architecture Excellent time management and organizational skills Requirements: Bachelor's degree in computer science, data science, mathematics, or a related field. Master’s degree in computational linguistics, data analytics, or similar will be advantageous. At least two years' experience as a machine learning engineer. Advanced proficiency with Python, Java, and C code writing. In-depth knowledge of Deep Learning and Machine Learning Algorithms. Strong knowledge of Kaldi, Speechbrain, Wespeaker, 3D-Speaker, Unispeech, Nemo etc. Proficiency in speaker verification, Speaker Identification, Speaker Diarization, Anti-spoofing. Strong programming and algorithm development skills. Ability to work independently and as part of a team. Basic knowledge in signal processing. Job Type: Full-time Pay: ₹700,000.00 - ₹1,000,000.00 per year Schedule: Day shift Work Location: In person Application Deadline: 12/07/2025

Job Summary: We are looking for a skilled Python Developer with 7 to 12 years of experience to design, develop, and maintain high-quality back-end systems and applications. The ideal candidate will have expertise in Python and related frameworks, with a focus on building scalable, secure, and efficient software solutions. This role requires a strong problem-solving mindset, collaboration with cross-functional teams, and a commitment to delivering innovative solutions that meet business objectives. Responsibilities Application and Back-End Development: Design, implement, and maintain back-end systems and APIs using Python frameworks such as Django, Flask, or FastAPI, focusing on scalability, security, and efficiency. Build and integrate scalable RESTful APIs, ensuring seamless interaction between front-end systems and back-end services. Write modular, reusable, and testable code following Python’s PEP 8 coding standards and industry best practices. Develop and optimize robust database schemas for relational and non-relational databases (e.g., PostgreSQL, MySQL, MongoDB), ensuring efficient data storage and retrieval. Leverage cloud platforms like AWS, Azure, or Google Cloud for deploying scalable back-end solutions. Implement caching mechanisms using tools like Redis or Memcached to optimize performance and reduce latency. AI/ML Development: Build, train, and deploy machine learning (ML) models for real-world applications, such as predictive analytics, anomaly detection, natural language processing (NLP), recommendation systems, and computer vision. Work with popular machine learning and AI libraries/frameworks, including TensorFlow, PyTorch, Keras, and scikit-learn, to design custom models tailored to business needs. Process, clean, and analyze large datasets using Python tools such as Pandas, NumPy, and PySpark to enable efficient data preparation and feature engineering. Develop and maintain pipelines for data preprocessing, model training, validation, and deployment using tools like MLflow, Apache Airflow, or Kubeflow. Deploy AI/ML models into production environments and expose them as RESTful or GraphQL APIs for integration with other services. Optimize machine learning models to reduce computational costs and ensure smooth operation in production systems. Collaborate with data scientists and analysts to validate models, assess their performance, and ensure their alignment with business objectives. Implement model monitoring and lifecycle management to maintain accuracy over time, addressing data drift and retraining models as necessary. Experiment with cutting-edge AI techniques such as deep learning, reinforcement learning, and generative models to identify innovative solutions for complex challenges. Ensure ethical AI practices, including transparency, bias mitigation, and fairness in deployed models. Performance Optimization and Debugging: Identify and resolve performance bottlenecks in applications and APIs to enhance efficiency. Use profiling tools to debug and optimize code for memory and speed improvements. Implement caching mechanisms to reduce latency and improve application responsiveness. Testing, Deployment, and Maintenance: Write and maintain unit tests, integration tests, and end-to-end tests using Pytest, Unittest, or Nose. Collaborate on setting up CI/CD pipelines to automate testing, building, and deployment processes. Deploy and manage applications in production environments with a focus on security, monitoring, and reliability. Monitor and troubleshoot live systems, ensuring uptime and responsiveness. Collaboration and Teamwork: Work closely with front-end developers, designers, and product managers to implement new features and resolve issues. Participate in Agile ceremonies, including sprint planning, stand-ups, and retrospectives, to ensure smooth project delivery. Provide mentorship and technical guidance to junior developers, promoting best practices and continuous improvement. Required Skills and Qualifications Technical Expertise: Strong proficiency in Python and its core libraries, with hands-on experience in frameworks such as Django, Flask, or FastAPI. Solid understanding of RESTful API development, integration, and optimization. Experience working with relational and non-relational databases (e.g., PostgreSQL, MySQL, MongoDB). Familiarity with containerization tools like Docker and orchestration platforms like Kubernetes. Expertise in using Git for version control and collaborating in distributed teams. Knowledge of CI/CD pipelines and tools like Jenkins, GitHub Actions, or CircleCI. Strong understanding of software development principles, including OOP, design patterns, and MVC architecture. Preferred Skills: Experience with asynchronous programming using libraries like asyncio, Celery, or RabbitMQ. Knowledge of data visualization tools (e.g., Matplotlib, Seaborn, Plotly) for generating insights. Exposure to machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) is a plus. Familiarity with big data frameworks like Apache Spark or Hadoop. Experience with serverless architecture using AWS Lambda, Azure Functions, or Google Cloud Run. Soft Skills: Strong problem-solving abilities with a keen eye for detail and quality. Excellent communication skills to effectively collaborate with cross-functional teams. Adaptability to changing project requirements and emerging technologies. Self-motivated with a passion for continuous learning and innovation. Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field. Job Features Job Category Software Division

Job Summary: We are looking for a skilled Python Developer with 3 to 6 years of experience to design, develop, and maintain high-quality back-end systems and applications. The ideal candidate will have expertise in Python and related frameworks, with a focus on building scalable, secure, and efficient software solutions. This role requires a strong problem-solving mindset, collaboration with cross-functional teams, and a commitment to delivering innovative solutions that meet business objectives. Responsibilities Application and Back-End Development: Design, implement, and maintain back-end systems and APIs using Python frameworks such as Django, Flask, or FastAPI, focusing on scalability, security, and efficiency. Build and integrate scalable RESTful APIs, ensuring seamless interaction between front-end systems and back-end services. Write modular, reusable, and testable code following Python’s PEP 8 coding standards and industry best practices. Develop and optimize robust database schemas for relational and non-relational databases (e.g., PostgreSQL, MySQL, MongoDB), ensuring efficient data storage and retrieval. Leverage cloud platforms like AWS, Azure, or Google Cloud for deploying scalable back-end solutions. Implement caching mechanisms using tools like Redis or Memcached to optimize performance and reduce latency. AI/ML Development: Build, train, and deploy machine learning (ML) models for real-world applications, such as predictive analytics, anomaly detection, natural language processing (NLP), recommendation systems, and computer vision. Work with popular machine learning and AI libraries/frameworks, including TensorFlow, PyTorch, Keras, and scikit-learn, to design custom models tailored to business needs. Process, clean, and analyze large datasets using Python tools such as Pandas, NumPy, and PySpark to enable efficient data preparation and feature engineering. Develop and maintain pipelines for data preprocessing, model training, validation, and deployment using tools like MLflow, Apache Airflow, or Kubeflow. Deploy AI/ML models into production environments and expose them as RESTful or GraphQL APIs for integration with other services. Optimize machine learning models to reduce computational costs and ensure smooth operation in production systems. Collaborate with data scientists and analysts to validate models, assess their performance, and ensure their alignment with business objectives. Implement model monitoring and lifecycle management to maintain accuracy over time, addressing data drift and retraining models as necessary. Experiment with cutting-edge AI techniques such as deep learning, reinforcement learning, and generative models to identify innovative solutions for complex challenges. Ensure ethical AI practices, including transparency, bias mitigation, and fairness in deployed models. Performance Optimization and Debugging: Identify and resolve performance bottlenecks in applications and APIs to enhance efficiency. Use profiling tools to debug and optimize code for memory and speed improvements. Implement caching mechanisms to reduce latency and improve application responsiveness. Testing, Deployment, and Maintenance: Write and maintain unit tests, integration tests, and end-to-end tests using Pytest, Unittest, or Nose. Collaborate on setting up CI/CD pipelines to automate testing, building, and deployment processes. Deploy and manage applications in production environments with a focus on security, monitoring, and reliability. Monitor and troubleshoot live systems, ensuring uptime and responsiveness. Collaboration and Teamwork: Work closely with front-end developers, designers, and product managers to implement new features and resolve issues. Participate in Agile ceremonies, including sprint planning, stand-ups, and retrospectives, to ensure smooth project delivery. Provide mentorship and technical guidance to junior developers, promoting best practices and continuous improvement. Required Skills and Qualifications Technical Expertise: Strong proficiency in Python and its core libraries, with hands-on experience in frameworks such as Django, Flask, or FastAPI. Solid understanding of RESTful API development, integration, and optimization. Experience working with relational and non-relational databases (e.g., PostgreSQL, MySQL, MongoDB). Familiarity with containerization tools like Docker and orchestration platforms like Kubernetes. Expertise in using Git for version control and collaborating in distributed teams. Knowledge of CI/CD pipelines and tools like Jenkins, GitHub Actions, or CircleCI. Strong understanding of software development principles, including OOP, design patterns, and MVC architecture. Preferred Skills: Experience with asynchronous programming using libraries like asyncio, Celery, or RabbitMQ. Knowledge of data visualization tools (e.g., Matplotlib, Seaborn, Plotly) for generating insights. Exposure to machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) is a plus. Familiarity with big data frameworks like Apache Spark or Hadoop. Experience with serverless architecture using AWS Lambda, Azure Functions, or Google Cloud Run. Soft Skills: Strong problem-solving abilities with a keen eye for detail and quality. Excellent communication skills to effectively collaborate with cross-functional teams. Adaptability to changing project requirements and emerging technologies. Self-motivated with a passion for continuous learning and innovation. Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field. Job Features Job Category Software Division

Job Title - Python AL/ML Developer Experience - 4+ years Location - Indore (WFO) Np - Immediate/15 days Job description -Implement proof of concepts in Engineering Systems and other innovation field topics where ML / AI technologies can be applied. Realize ML / AI product features. -You will be involved in coding of features, POC s and/or bug-fixing and delivering solutions adhering to coding and quality guidelines. -You will be responsible for Implementation of features and/or bug-fixing and delivering solutions in accordance with coding guidelines and on-time with high quality. -You will be responsible for Identification and implementation of unit and integration tests to ensure solution addresses customer requirements, and quality, security requirements of product are met. -You will be responsible for Ensuring integration and submission of solution into software configuration management system, within committed delivery timelines. -Experience on Large Language Models (LLMs) such as BERT and LLAMA. -Language Model Development: Utilize off-the-shelf LLM services, like Azure OpenAI, for integrating LLM capabilities into applications, and develop new language models. -Model Training and Evaluation: Train and fine-tune language models using appropriate machine-learning frameworks and tools. Experience -3+ years of experience in the following -Strong programming ability in both scripting and object-oriented programming languages is required (python) -Strong working knowledge in Deep learning and ML Algorithms. -Strong working knowledge in Tensor Flow, Sci-kit Learn, KERAS, Caffe, Pandas, NumPy, PyTorch, Matplotli -Knowledge in Natural language processing (NLP) & Deep Learning is required. -Software Design & Development - OOPS/OOAD methodologies

Job Description: Anti-Spoofing/Liveness Detection Engineer The Anti-Spoofing/Liveness Detection Engineer focuses on developing advanced systems to detect and prevent spoofing attacks during biometric authentication processes. This role involves utilizing machine learning and deep learning techniques to create models capable of distinguishing between genuine human interactions and fraudulent attempts. Main Responsibilities  - Liveness Detection System Design: Develop and design liveness detection systems that utilize AI algorithms to differentiate between real and fake biometric data. This includes analyzing facial features, eye movements, and other physiological indicators. - Deep Learning Model Development : Build and optimize deep learning models specifically for liveness detection. This ivolves selecting appropriate algorithms, conducting experiments, and optimizing model parameters to enhance accuracy and reliability. - Feature Engineering: Identify and extract features from biometric data that are crucial for detecting spoofing attempts. This includes texture analysis, motion-based detection, and 3D depth analysis. - Data Collection and Preprocessing: Collaborate with data scientists to collect, clean, and preprocess large datasets required for training liveness detection models. Ensure data integrity and suitability for model development. - Algorithm Implementation: Implement machine learning algorithms capable of processing realtime biometric data to detect inconsistencies indicative of spoofing attempts. This includes integrating multimodal approaches such as facial recognition, fingerprint scanning, and iris recognition. - System Testing and Validation: Conduct rigorous testing of liveness detection systems to ensure performance in real-world scenarios. Validate models against various spoofing techniques to ensure robustness. - Monitoring and Maintenance: Deploy liveness detection systems into production environments, ensuring scalability and high performance. Continuously monitor system outputs to identify any issues with accuracy or efficiency. Required Skills - Machine Learning Expertise: In-depth understanding of machine learning frameworks such as TensorFlow, Keras, or PyTorch. Experience in developing deep learning models is essential. - Programming Skills: Proficiency in programming languages such as Python, Java, or R for model development and algorithm implementation. - Analytical Skills: Strong problem-solving abilities with a solid grasp of statistics, probability theory, and data analysis techniques. - Collaboration Skills : Ability to work effectively with cross-functional teams (including data scientists, software engineers, and product managers) to achieve common goals. Preferred Qualifications - Experience in similar roles focusing on anti-spoofing or biometric security systems. - Bachelor's degree in Computer Science, Mathematics, or a related field. - Familiarity with anti-spoofing standards for biometrics such as NIST ISO/IEC 30107 or FIDO. - Innovative mindset with a passion for continuous learning and keeping up with the latest advancements in AI and machine learning technologies.

Artificial Intelligence & Machine Learning Intern (Remote | 3 Months) Company: INLIGHN TECH Location: Remote Duration: 3 Months Stipend (Top Performers): ₹15,000 Perks: Certificate | Letter of Recommendation | Hands-on Training About INLIGHN TECH INLIGHN TECH empowers students and recent graduates through hands-on, project-based internships. Our AI & ML Internship is tailored to develop your expertise in building intelligent systems using real-world datasets and machine learning algorithms. Role Overview As an AI & ML Intern, you’ll work on projects involving model development, data preprocessing, and algorithm implementation. You'll gain practical experience applying artificial intelligence concepts to solve real business problems. Key Responsibilities Collect and preprocess structured and unstructured data Implement supervised and unsupervised machine learning algorithms Work on deep learning models using frameworks like TensorFlow or PyTorch Evaluate model performance and tune hyperparameters Develop intelligent solutions and predictive systems Collaborate with peers on AI-driven projects Requirements Pursuing or recently completed a degree in Computer Science, AI, Data Science, or a related field Proficient in Python and libraries such as Pandas, NumPy, Scikit-learn Familiar with machine learning and deep learning concepts Knowledge of TensorFlow, Keras, or PyTorch is a plus Strong mathematical and analytical thinking Enthusiastic about AI/ML innovations and eager to learn What You’ll Gain Real-world experience developing AI and ML models Internship Completion Certificate Letter of Recommendation for high-performing interns Portfolio of AI/ML projects for career building Potential full-time offer based on performance