7754 Tensorflow Jobs - Page 25

Job Title:Artificial Intelligence EngineerExperience8-12 YearsLocation:Bangalore : Algorithm Development**Design and implement algorithms, neural networks, and other machine learning techniques to simulate human intelligence processes. Model Creation**Develop and validate algorithms, neural networks, and other machine learning models. Generative AI**Specialize in generative AI, which involves creating AI systems that autonomously generate content such as text, images, and music. Machine Learning**Leverage your expertise in machine learning to train models on large datasets and optimize them for creative content generation. Natural Language Processing (NLP)**Apply NLP techniques for text generation projects, including text parsing, sentiment analysis, and the use of transformer models like GPT. Data Management**Handle data pre-processing, augmentation, and synthetic data generation. Qualifications To excel in this role, you should possess the following skills: Hard Skills1. **Advanced Programming**Proficiency in programming languages such as Python, along with AI-centric libraries like TensorFlow, PyTorch, and Keras.2. **Generative Models**Expertise in generative models, including Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).3. **NLP**Familiarity with NLP techniques for text generation.4. **Data Management**Knowledge of data pre-processing, augmentation, and synthetic data generation.Soft Skills1. **Creativity**Ability to think creatively and solve complex, creative challenges using AI.2. **Collaboration**Work effectively with researchers, engineers, and other team members.3. **Continuous Learning**Stay updated with evolving AI technologies and applications.Qualifications- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related fields.- Proven experience in machine learning, generative AI,

Job Title:GenAI SpecialistExperience4-8 YearsLocation:Bangalore : We are looking for a GenAI specialist withexperience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. Develop and implement AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems preferably in security area. Additionally, expertise in cyber security, data engineering, DevOps, and MLOps practices will be valuable in this role Position Summary Contribute to the design and implementation of state-of-the-art AI solutions. Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Skills: Minimum 4 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Qualification: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Certification: NA Skills PRIMARY COMPETENCY Information Security PRIMARY Cyber Security for Cloud PRIMARY PERCENTAGE 100

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Software Engineer II We are the global technology company behind the world’s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. The Mastercard Launch program is aimed at early career talent, to help you develop skills and gain cross-functional work experience. Over a period of 18 months, Launch participants will be assigned to a business unit, learn and develop skills, and gain valuable on the job experience. Mastercard has over 2 billion payment cards issued by 25,000+ banks across 190+ countries and territories, amassing over 10 petabytes of data. Millions of transactions are flowing to Mastercard in real-time providing an ideal environment to apply and leverage AI at scale. The AI team is responsible for building and deploying innovative AI solutions for all divisions within Mastercard securing a competitive advantage. Our objectives include achieving operational efficiency, improving customer experience, and ensuring robust value propositions of our core products (Credit, Debit, Prepaid) and services (recommendation engine, anti-money laundering, fraud risk management, cybersecurity) Role Gather relevant information to define the business problem Creative thinker capable of linking AI methodologies to identified business challenges Develop AI/ML applications leveraging the latest industry and academic advancements Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda All About You : Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Concentration in Computer Science Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. R-251749

Job Summary As the Technical Squad Lead, Central Platform Development, you will play a critical role in making the internal state of the bank's application and infrastructure services visible to stakeholders for troubleshooting, performance analysis, capacity planning, and reporting through the Central Monitoring and Observability Platform. You will lead to develop the bank’s central monitoring and observability platform and tooling to enable product owners, developers, and operators to efficiently trace performance problems to their source and map their application performance to business objectives. You will lead the Predictive Monitoring and Predictive Observability and AIOps practices for the platform to enable observability platform to predict issues early. Key Responsibilities Strategy Awareness and understanding of the TTO’25 business strategy and model appropriate to the role. Support and the enablement of the Central Monitoring & Observability strategy, goals and objectives by developing prioritized features aligned to the Catalyst and Tech Simplification programmes Business The Monitoring & Observability Platform team is a global team ensuring the design, development, delivery & support of the bank’s central monitoring and observability services for all TTO teams (technology domains). The ideal candidate will possess a deep understanding in one or more of the Observability technologies (Elastic Observability, Grafana Observability) and AIOps Specialist, Data Specialist, Machine Learning Engineer, Data Transformation Lead, enabling the design, development, implementation, and management of the machine learning frameworks, integrating advanced technological tools and techniques, with a strong focus on applying ML techniques to real-world problems. Participation in Weekend releases, overnight major incidents to help teams enable Observability Predictive Capability is a must as this is key capability for the role. Must have working experience on AIOps and MLOps Processes As the Technical Squad Lead, Central Platform Development, you will play a crucial role in ensuring the stability, reliability, and use of Machine learning of our applications and platform integrations, thereby enabling our organization to deliver predictive observability services to our internal stakeholders by adhering to the Enterprise SDLC (eSDLC) framework and guidelines. Responsibilities People & Talent Actively engaging in stakeholders’ conversations, providing timely, clear and actionable feedback to deliver solution within timeline. Risk Management The ability to interpret the Group’s technical and security (ICS) control requirements and information to identify potential risks and key issues based on this information and put in place appropriate controls and measures to mitigate or minimize risk to the central monitoring & observability platform delivery Governance Awareness and understanding of the eSDLC framework, in which the TTO software delivery operates, and the requirements and expectations relevant to the role. Responsible for adhering to the effectiveness of the central monitoring and observability platform deliver governance, based on oversight and controls of the eSDLC framework. Responsibilities Regulatory & Business Conduct Display exemplary conduct and live by the Group’s Values and Code of Conduct. Take personal responsibility for embedding the highest standards of ethics, including regulatory and business conduct, across Standard Chartered Bank. This includes understanding and ensuring compliance with, in letter and spirit, all applicable laws, regulations, guidelines and the Group Code of Conduct. Effectively and collaboratively identify, escalate, mitigate and resolve risk, conduct and compliance matters Key stakeholders TTO CIO Development teams TTO Product Owners TTO SRE / PSS TTO Cloud Engineering ET Foundation Service Owners Other Responsibilities Participate in solution architecture / design consulting, platform management, and capacity planning activities. Create sustainable solutions and services through automation and service uplifts within monitoring and observability disciplines. Participation in Weekend releases, overnight major incidents to help teams enable Observability Predictive Capability is a must. Skills And Experience Our ideal candidate should have overall minimum of 8+ years of IT experience. Bachelor’s Degree in computer science or Information Systems or equivalent applicable experience Proven experience (4 years) working as an Observability/Monitoring Specialist, AIOPs specialist, Data Transformation Lead or similar role, with a strong focus on applying observability techniques to real-world problems to reduce incident impacts. Design and develop AI-powered solutions for Observability using Machine Learning techniques and rightful used models. Must have experience on mentoring team in terms of creating structure to the book of work. Help team with organised product backlog. Participation in Weekend releases, overnight major incidents to help teams enable Observability Predictive Capability is a must as this is key capability for the role. Hands-on experience with machine learning frameworks (e.g., TensorFlow, PyTorch,SKLearn, XGboost etc.) and proficiency in programming languages such as Python, Hive, Spark, Pyspark etc. Working experience in AIOps by creating Data ingestion ETL pipelines, aggregation, analytics and Machine Learning. Must have working experience on AIOps and MLOps using traditional and Gen-AI LLM models such as Mistral, Llama, Bert. Enables Use of AI in responsible way and enable AI, ML technologies to identify historical trends, dynamic baselining and to drive Root cause analysis actions. Enables Use of Machine Learning as an assistant to enable observability analysts, product owners, incident managers, hive leads to come with right actions. Addressed problems through risk management and contingency planning. Software development life cycle knowledge in terms of analysis, development & testing phases. Qualifications Education: Degree Training: Agile Delivery, DevOps, Predictive Monitoring Certifications: Machine Learning, AIOps Languages: English Role Specific Technical Competencies Agile Delivery Application Delivery Process AIOps Specialist, Machine Learning Frameworks Software Product Technical Knowledge Monitoring and Observability Experience Data Pipelines Application Programming, Integration About Standard Chartered We're an international bank, nimble enough to act, big enough for impact. For more than 170 years, we've worked to make a positive difference for our clients, communities, and each other. We question the status quo, love a challenge and enjoy finding new opportunities to grow and do better than before. If you're looking for a career with purpose and you want to work for a bank making a difference, we want to hear from you. You can count on us to celebrate your unique talents and we can't wait to see the talents you can bring us. Our purpose, to drive commerce and prosperity through our unique diversity, together with our brand promise, to be here for good are achieved by how we each live our valued behaviours. When you work with us, you'll see how we value difference and advocate inclusion. Together We: Do the right thing and are assertive, challenge one another, and live with integrity, while putting the client at the heart of what we do Never settle, continuously striving to improve and innovate, keeping things simple and learning from doing well, and not so well Are better together, we can be ourselves, be inclusive, see more good in others, and work collectively to build for the long term What We Offer In line with our Fair Pay Charter, we offer a competitive salary and benefits to support your mental, physical, financial and social wellbeing. Core bank funding for retirement savings, medical and life insurance, with flexible and voluntary benefits available in some locations. Time-off including annual leave, parental/maternity (20 weeks), sabbatical (12 months maximum) and volunteering leave (3 days), along with minimum global standards for annual and public holiday, which is combined to 30 days minimum. Flexible working options based around home and office locations, with flexible working patterns. Proactive wellbeing support through Unmind, a market-leading digital wellbeing platform, development courses for resilience and other human skills, global Employee Assistance Programme, sick leave, mental health first-aiders and all sorts of self-help toolkits A continuous learning culture to support your growth, with opportunities to reskill and upskill and access to physical, virtual and digital learning. Being part of an inclusive and values driven organisation, one that embraces and celebrates our unique diversity, across our teams, business functions and geographies - everyone feels respected and can realise their full potential.

Job Summary Experience in applying machine learning techniques, Natural Language Processing or Computer Vision using TensorFlow, Pytorch Strong analytical and problem-solving skills Solid software engineering skills across multiple languages including but not limited to Java or Python, C/C++ Build and deploy end to end ML models and leverage metrics to support predictions, recommendations, search, and growth strategies Deep understanding of ML techniques such as: classification, clustering, deep learning, optimization methods, supervised and unsupervised techniques Proven ability to apply, debug, and develop machine learning models Establish scalable, efficient, automated processes for data analyses, model development, validation and implementation, Choose suitable DL algorithms, software, hardware and suggest integration methods. Ensure AI ML solutions are developed, and validations are performed in accordance with Responsible AI guidelines & Standards To closely monitor the Model Performance and ensure Model Improvements are done post Project Delivery Coach and mentor our team as we build scalable machine learning solutions Strong communication skills and an easy-going attitude Oversee development and implementation of assigned programs and guide teammates Carry out testing procedures to ensure systems are running smoothly Ensure that systems satisfy quality standards and procedures Build and manage strong relationships with stakeholders and various teams internally and externally, Provide direction and structure to assigned projects activities, establishing clear, precise goals, objectives and timeframes, run Project Governance calls with senior Stakeholders Key Responsibilities Strategy As the Squad Lead of AI ML Delivery team, the candidate is expected to lead the squad Delivery for AIML. Business Understand the Business requirement and execute the ML solutioning and ensue the delivery commitments are delivered on time and schedule. Processes Design and Delivery of AI ML Use cases RAI, Security & Governance Model Validation & Improvements Stakeholder Management People & Talent Manage the team in terms of project assignments and deadlines Manage a team dedicated for reviewing models related unstructured and structured data. Hire, nurture talent as required. Risk Management Ownership of the delivery, highlighting various risks on a timely manner to the stakeholders. Identifying proper remediation plan for the risks with proper risk roadmap. Governance Awareness and understanding of the regulatory framework, in which the Group operates, and the regulatory requirements and expectations relevant to the role. Regulatory & Business Conduct Display exemplary conduct and live by the Group’s Values and Code of Conduct. Take personal responsibility for embedding the highest standards of ethics, including regulatory and business conduct, across Standard Chartered Bank. This includes understanding and ensuring compliance with, in letter and spirit, all applicable laws, regulations, guidelines and the Group Code of Conduct. Lead to achieve the outcomes set out in the Bank’s Conduct Principles Effectively and collaboratively identify, escalate, mitigate and resolve risk, conduct and compliance matters Key stakeholders Business Stakeholders AIML Engineering Team AIML Product Team Product Enablement Team SCB Infrastructure Team Qualifications Masters with specialisation in Technology with certification in AI and ML 8- 12 years relevant of Hands-on Experience in developing and delivering AI solutions Skills And Experience Use NLP, Vision and ML techniques to bring order to unstructured data Experience in extracting signal from noise in large unstructured datasets a plus Work within the Engineering Team to design, code, train, test, deploy and iterate on enterprise scale machine learning systems Work alongside an excellent, cross-functional team across Engineering, Product and Design create solutions and try various algorithms to solve the problem. Stakeholder Management About Standard Chartered We're an international bank, nimble enough to act, big enough for impact. For more than 170 years, we've worked to make a positive difference for our clients, communities, and each other. We question the status quo, love a challenge and enjoy finding new opportunities to grow and do better than before. If you're looking for a career with purpose and you want to work for a bank making a difference, we want to hear from you. You can count on us to celebrate your unique talents and we can't wait to see the talents you can bring us. Our purpose, to drive commerce and prosperity through our unique diversity, together with our brand promise, to be here for good are achieved by how we each live our valued behaviours. When you work with us, you'll see how we value difference and advocate inclusion. Together We Do the right thing and are assertive, challenge one another, and live with integrity, while putting the client at the heart of what we do Never settle, continuously striving to improve and innovate, keeping things simple and learning from doing well, and not so well Are better together, we can be ourselves, be inclusive, see more good in others, and work collectively to build for the long term What We Offer In line with our Fair Pay Charter, we offer a competitive salary and benefits to support your mental, physical, financial and social wellbeing. Core bank funding for retirement savings, medical and life insurance, with flexible and voluntary benefits available in some locations. Time-off including annual leave, parental/maternity (20 weeks), sabbatical (12 months maximum) and volunteering leave (3 days), along with minimum global standards for annual and public holiday, which is combined to 30 days minimum. Flexible working options based around home and office locations, with flexible working patterns. Proactive wellbeing support through Unmind, a market-leading digital wellbeing platform, development courses for resilience and other human skills, global Employee Assistance Programme, sick leave, mental health first-aiders and all sorts of self-help toolkits A continuous learning culture to support your growth, with opportunities to reskill and upskill and access to physical, virtual and digital learning. Being part of an inclusive and values driven organisation, one that embraces and celebrates our unique diversity, across our teams, business functions and geographies - everyone feels respected and can realise their full potential.

Job Summary Experience in applying machine learning techniques, Natural Language Processing or Computer Vision using TensorFlow, Pytorch, Gen AI – LLM , AI Agentic framework Strong analytical and problem-solving skills Solid software engineering skills across multiple languages including but not limited to Java or Python, C/C++ Build and deploy end to end ML models and leverage metrics to support predictions, recommendations, search, and growth strategies Deep understanding of ML techniques such as: classification, clustering, deep learning, optimization methods, supervised and unsupervised techniques Proven ability to apply, debug, and develop machine learning models Establish scalable, efficient, automated processes for data analyses, model development, validation and implementation, Choose suitable DL algorithms, software, hardware and suggest integration methods. Ensure AI ML solutions are developed, and validations are performed in accordance with Responsible AI guidelines & Standards To closely monitor the Model Performance and ensure Model Improvements are done post Project Delivery Coach and mentor our team as we build scalable machine learning solutions Strong communication skills and an easy-going attitude Oversee development and implementation of assigned programs and guide teammates Carry out testing procedures to ensure systems are running smoothly Ensure that systems satisfy quality standards and procedures Build and manage strong relationships with stakeholders and various teams internally and externally, Provide direction and structure to assigned projects activities, establishing clear, precise goals, objectives and timeframes, run Project Governance calls with senior Stakeholders Key Responsibilities Business Understand the Business requirement and execute the ML solutioning and ensue the delivery commitments are delivered on time and schedule. Processes Design and Delivery of AI ML Product features. RAI, Security & Governance Model Validation & Improvements Stakeholder Management Risk Management Ownership of the delivery, highlighting various risks on a timely manner to the stakeholders. Identifying proper remediation plan for the risks with proper risk roadmap. Governance Awareness and understanding of the regulatory framework, in which the Group operates, and the regulatory requirements and expectations relevant to the role. Regulatory & Business Conduct Display exemplary conduct and live by the Group’s Values and Code of Conduct. Take personal responsibility for embedding the highest standards of ethics, including regulatory and business conduct, across Standard Chartered Bank. This includes understanding and ensuring compliance with, in letter and spirit, all applicable laws, regulations, guidelines and the Group Code of Conduct. Lead to achieve the outcomes set out in the Bank’s Conduct Principles Effectively and collaboratively identify, escalate, mitigate and resolve risk, conduct and compliance matters Key stakeholders Business Stakeholders AIML Engineering Team AIML Use case Team Product Enablement Team SCB Infrastructure Team Interfacing Program Team Qualifications Masters with specialisation in Technology with certification in AI and ML 8- 10 years relevant of Hands-on Experience in developing and delivering AI solutions Experience in Gen AI , LLM and agentic framework Role Specific Technical Competencies Use NLP, Vision and ML techniques to bring order to unstructured data Experience in solutioning and working on Gen AI – LLM use cases and knowledge on AI Agents Work within the Engineering Team to design, code, train, test, deploy and iterate on enterprise scale machine learning systems Work alongside an excellent, cross-functional team across Engineering, Product and Design create solutions and try various algorithms to solve the problem. Stakeholder Management About Standard Chartered We're an international bank, nimble enough to act, big enough for impact. For more than 170 years, we've worked to make a positive difference for our clients, communities, and each other. We question the status quo, love a challenge and enjoy finding new opportunities to grow and do better than before. If you're looking for a career with purpose and you want to work for a bank making a difference, we want to hear from you. You can count on us to celebrate your unique talents and we can't wait to see the talents you can bring us. Our purpose, to drive commerce and prosperity through our unique diversity, together with our brand promise, to be here for good are achieved by how we each live our valued behaviours. When you work with us, you'll see how we value difference and advocate inclusion. Together We Do the right thing and are assertive, challenge one another, and live with integrity, while putting the client at the heart of what we do Never settle, continuously striving to improve and innovate, keeping things simple and learning from doing well, and not so well Are better together, we can be ourselves, be inclusive, see more good in others, and work collectively to build for the long term What We Offer In line with our Fair Pay Charter, we offer a competitive salary and benefits to support your mental, physical, financial and social wellbeing. Core bank funding for retirement savings, medical and life insurance, with flexible and voluntary benefits available in some locations. Time-off including annual leave, parental/maternity (20 weeks), sabbatical (12 months maximum) and volunteering leave (3 days), along with minimum global standards for annual and public holiday, which is combined to 30 days minimum. Flexible working options based around home and office locations, with flexible working patterns. Proactive wellbeing support through Unmind, a market-leading digital wellbeing platform, development courses for resilience and other human skills, global Employee Assistance Programme, sick leave, mental health first-aiders and all sorts of self-help toolkits A continuous learning culture to support your growth, with opportunities to reskill and upskill and access to physical, virtual and digital learning. Being part of an inclusive and values driven organisation, one that embraces and celebrates our unique diversity, across our teams, business functions and geographies - everyone feels respected and can realise their full potential.

Looking for someone who thrives in a full-stack Python + QA + Database + AI environment and is excited to grow technically. If you’re a passionate Python engineer with 3–5 years of hands-on experience. You’ve built web services, supported QA/automation workflows, and worked confidently across SQL/NoSQL databases. Ideally, you’ve also experimented with AI/ML tooling or frameworks, so this opportunity is for you. Responsibilities Develop, test, and maintain Python-based backend services using Django , FastAPI , or Flask Execute efficient web scraping tasks using BeautifulSoup or Scrapy Automate browser workflows using Selenium Write scalable database queries and schema designs for SQL (PostgreSQL/MySQL) and MongoDB Design and implement QA automation scripts and frameworks (Optional but desirable) Integrate and utilize AI/ML tools , packages, or APIs Must-Have Skills Proficient in Python (3.x) and modern frameworks (Django/FastAPI/Flask) Web scraping experience with BeautifulSoup , Scrapy , or equivalent Hands-on automation using Selenium Strong database expertise in SQL and MongoDB Solid understanding of testing principles , automation techniques, and version control (Git) Nice-to-Have Exposure to AI or machine learning libraries (e.g. TensorFlow, PyTorch, OpenAI APIs) Familiarity with CI/CD pipelines (Jenkins, GitHub Actions) and containerization (Docker) Why This Role is Great Balanced challenge across backend development , QA automation , and data work Opportunity to explore AI/ML tools in real-world projects Engage in end-to-end ownership: backend → QA → deployment pipelines Job Location: Gurugram Work Model: On-site Budget: 15-18 LPA

Role Title: Data Scientist Function / Department: Corporate Digitalization and Analytics Location: Jogeshwari, Mumbai (On-Site) / Chennai (On-Site) About the Role: We are seeking an experienced Data Scientist (4-6 years) to lead AI-driven transformation in a globally recognized Pharma Manufacturing IIoT environment. Our AI/ML use cases have received recognition from the World Economic Forum's Global Lighthouse Network, making this a high-impact, innovation-driven role. This position involves leading multiple use cases, working on exploratory technologies, and experimenting with cutting-edge AI tools. The role also entails working on vision-based use cases using quadrupeds (robotic systems) for industrial automation and process optimization. Why Join Us? Be part of AI projects recognized by the World Economic Forum's Global Lighthouse Network. Lead AI-driven decision-making & automation in a high-impact, mission-critical pharma environment. Experiment with AI innovations & next-gen robotics (quadrupeds, computer vision). Collaborate with top industry experts in a future-focused, technology-driven environment. Key Responsibilities: Lead AI-Driven Use Cases: Develop and deploy machine learning models for predictive maintenance, yield optimization, and quality control. Computer Vision & Robotics Integration: Build and optimize vision-based analytics for Quadrupeds to automate inspections and detect anomalies. Cutting-Edge Generative AI & NLP: Implement Generative AI models (e.g., GANs, Transformers) for manufacturing insights and process automation. Big Data Processing & AI Pipelines: Work with IIoT data streams, industrial sensors, and unstructured datasets for scalable AI deployment. Interactive Analytics & Decision Intelligence: Develop high-impact dashboards and visualizations for leadership decision-making. Research & Experimentation: Explore and implement new AI tools and emerging technologies for digital transformation. Qualifications: Education: Bachelor's degree in Engineering or a Master's in Statistics, Computer Science, IT, Analytics, or related fields. Technical Skills: Programming: Proficiency in Python and libraries such as NumPy, pandas, scikit-learn. Machine Learning & Deep Learning: Experience with TensorFlow, PyTorch, and classical ML models. Computer Vision: Familiarity with OpenCV, object detection models, and industrial vision analytics. Generative AI: Exposure to GANs, NLP models, and Transformers. Big Data & IIoT: Experience with data pipelines, ETL processes, and IIoT data streams. Visualization: Expertise in Tableau, Power BI, or Plotly for interactive dashboards. Good to have: MLOps, Exposure to Azure or similar cloud platforms Skills and Competencies: Strategic Thinker: Ability to drive AI-powered decision-making in a fast-paced industrial setting. Tech Explorer: Passion for working on emerging AI technologies, robotics, and experimental AI models. Collaboration & Leadership: Comfortable working with cross-functional teams and leading projects. Problem-Solving Mindset: Strong analytical skills to handle complex industrial datasets and drive impact.

Our Company Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours! The Applied Research Team will work at the fore front of applying cutting-edge technologies in practical and user-centric applications. Their primary focus will be on implementing and optimizing generative AI solutions for a range of applications in graphics and design. This includes the development of sophisticated image processing techniques and the enhancement of human-computer interaction interfaces using machine learning algorithms. They will also be deeply involved in programming with languages like C++ and Python to develop robust, production-level software. The team will utilize machine learning frameworks such as TensorFlow and PyTorch, not only for model development but also for converting and deploying these models efficiently in production environments. Their work will be vital in transforming theoretical AI advancements into accessible, efficient, and impactful applications, constantly iterating and improving upon them to meet evolving user needs and industry standards. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more about our vision here. Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call (408) 536-3015.

Job Title: Data Scientist Location: Bengaluru, Gurugram Experience: 5+ Years About the Role: We are looking for an experienced Data Scientist to develop and deploy AI/ML and GenAI solutions across large datasets using modern frameworks and cloud infrastructure. You’ll work closely with cross-functional teams to translate business requirements into impactful data products. Key Responsibilities: Collaborate with software engineers, stakeholders, and domain experts to define data-driven solutions. Develop, implement, and deploy AI/ML, NLP/NLU, and deep learning models. Work on preprocessing, analyzing large datasets, and deriving actionable insights. Evaluate and optimize models for performance, efficiency, and scalability. Deploy solutions to cloud platforms such as Azure (preferred), AWS, or GCP. Monitor production models and iterate for continuous improvement. Document processes, results, and best practices. Must-Have Skills: Bachelor's/Master’s in Computer Science, Data Science, Engineering, or related field. Strong programming in Python and SQL . Experience with Scikit-learn, TensorFlow, PyTorch , etc. Knowledge of ETL tools like Azure Data Factory , Databricks , Data Lake . Solid foundation in mathematics, probability, and statistics . Exposure to GenAI , Vector Databases , and LLMs . Experience working with cloud infrastructure ( Azure preferred ). Good-to-Have Skills: Experience with Flask , Django , or Streamlit . Knowledge of MLOps tools : MLFlow, Kubeflow, CI/CD. Familiarity with Docker , Kubernetes for model/container deployment. #teceze

Job Summary We are looking for a dynamic and knowledgeable AI & Machine Learning in Healthcare Trainer to deliver a 3-month career-oriented training program. The ideal candidate will possess strong expertise in machine learning, clinical data analytics, and visualization tools like SQL, Power BI, and Tableau, with hands-on experience in real-world healthcare environments. Key Responsibilities • Deliver structured training on AI/ML concepts applied to healthcare, including real datasets and use cases • Teach practical hands-on labs using Python (NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch) • Introduce learners to healthcare data analysis using SQL, Power BI, and Tableau • Cover applications such as predictive analytics, medical imaging AI, EHR NLP, and disease modeling • Guide learners through data extraction, cleaning, and visual storytelling from healthcare datasets • Discuss ethical and legal challenges in AI, including bias mitigation, HIPAA, and GDPR • Evaluate student progress, provide feedback, and support capstone projects • Update training materials based on healthcare tech advancements and student needs Required Skills & Knowledge Category Skills & Tools AI/ML Fundamentals Regression, classification, clustering, model evaluation Programming Python, NumPy, Pandas, Scikit-learn, TensorFlow or PyTorch Data Handling Healthcare datasets (MIMIC, HL7/FHIR, claims data), data wrangling, cleaning NLP in Healthcare Text preprocessing, spaCy, BioBERT, cTAKES SQL & Databases Writing queries, joins, data aggregation, healthcare-specific schemas Power BI & Tableau Data modeling, interactive dashboards, storytelling with healthcare KPIs Teaching & Communication Ability to simplify technical content, present with clarity, use visual examples Preferred Qualifications • Master’s in Data Science, Computer Science, Bioinformatics, or related field • Prior teaching, mentoring, or curriculum development experience • Certifications in Tableau, Power BI, TensorFlow, or Google AI (preferred) What We Offer Competitve salary based on experience

Main Purpose: • Data engineering - Source data from internal system sources and external (public/private) sources, using data pipelines or automations • Data science & risk modelling - Develop risk models / algorithm for calculating credit scoring of clients, credit loss, simulating stress scenarios and LLM models to aide credit risk assessment • Risk Reporting & Visualization - Develop risk reports and dashboards for credit risk officers to analyse and monitor risks in their portfolio • Data governance - Organise and document data attributes, process and procedures • Infrastructure management - Collaborate with internal technology teams to analyse impact on data due to infrastructure changes • To understanding trade Life Cycle – work closely with key departments across the organization, including Accounting, Trade Finance, Operations, and Deal Desk (amongst others) to understand data throughout the trade life cycle Knowledge Skills and Abilities, Key Responsibilities: Bachelor’s degree in computer science, Finance, Mathematics, Statistics, or related field 3-5 years of experience in data engineering, data science, or similar technical role Proficiency in SQL and database management systems Strong programming skills in Python, R, or similar languages for statistical analysis and machine learning Experience with machine learning frameworks (scikit-learn, TensorFlow, PyTorch) Knowledge of statistical modeling, econometrics, and risk management methodologies Experience with ETL/ELT tools and data pipeline frameworks Familiarity with Large Language Models and Natural Language Processing techniques Experience with data visualization tools (Tableau, Power BI, or similar) Excellent English verbal and written communication Key Responsibilities: Data Engineering: Design, build, and maintain robust data pipelines to source data from internal system sources and external public/private data providers Develop automated data ingestion processes to ensure timely and accurate data flow Implement data quality controls and monitoring systems to maintain data integrity Data Science & Risk Modelling: Develop and maintain sophisticated risk models and algorithms for calculating client credit scores Build predictive models for credit loss estimation and expected credit loss calculations Design and implement stress testing scenarios to evaluate portfolio resilience under adverse conditions Create and deploy Large Language Model (LLM) solutions to enhance credit risk assessment processes Risk Reporting & Visualization: Develop comprehensive risk reports and interactive dashboards for credit risk officers Create visualization tools that enable effective portfolio risk analysis and monitoring Data governance: Organise and document data attributes, process and procedures Infrastructure management: Collaborate with internal technology teams to analyse impact on data due to infrastructure changes Trade Life Cycle: Work closely with key departments across the organization, including Accounting, Trade Finance, Operations, and Deal Desk (amongst others) to understand data throughout the trade life cycle Key Relationships Global Credit team, risk technology, data scientist, Other internal departments (accounts, treasury, trade finance, operations etc) Key Relationships and Department Overview: Global Credit team, Head of Operation Risk Management, Other internal departments (accounts, treasury, trade finance, operations etc)

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Software Engineer II We are the global technology company behind the world’s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. The Mastercard Launch program is aimed at early career talent, to help you develop skills and gain cross-functional work experience. Over a period of 18 months, Launch participants will be assigned to a business unit, learn and develop skills, and gain valuable on the job experience. Mastercard has over 2 billion payment cards issued by 25,000+ banks across 190+ countries and territories, amassing over 10 petabytes of data. Millions of transactions are flowing to Mastercard in real-time providing an ideal environment to apply and leverage AI at scale. The AI team is responsible for building and deploying innovative AI solutions for all divisions within Mastercard securing a competitive advantage. Our objectives include achieving operational efficiency, improving customer experience, and ensuring robust value propositions of our core products (Credit, Debit, Prepaid) and services (recommendation engine, anti-money laundering, fraud risk management, cybersecurity) Role Gather relevant information to define the business problem Creative thinker capable of linking AI methodologies to identified business challenges Develop AI/ML applications leveraging the latest industry and academic advancements Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda All About You : Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Concentration in Computer Science Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. R-251749

Our Company Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours! The Applied Research Team will work at the fore front of applying cutting-edge technologies in practical and user-centric applications. Their primary focus will be on implementing and optimizing generative AI solutions for a range of applications in graphics and design. This includes the development of sophisticated image processing techniques and the enhancement of human-computer interaction interfaces using machine learning algorithms. They will also be deeply involved in programming with languages like C++ and Python to develop robust, production-level software. The team will utilize machine learning frameworks such as TensorFlow and PyTorch, not only for model development but also for converting and deploying these models efficiently in production environments. Their work will be vital in transforming theoretical AI advancements into accessible, efficient, and impactful applications, constantly iterating and improving upon them to meet evolving user needs and industry standards. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more about our vision here. Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call (408) 536-3015.

Summary: We are seeking a talented and motivated AI Engineer to join our team and focus on building cutting-edge Generative AI applications. The ideal candidate will possess a strong background in data science, machine learning, and deep learning, with specific experience in developing and fine-tuning Large Language Models (LLMs) and Small Language Models (SLMs). You should be comfortable managing the full lifecycle of AI projects, from initial design and data handling to deployment and production monitoring. A foundational understanding of software engineering principles is also required to collaborate effectively with engineering teams and ensure robust deployments. Responsibilities: Design, develop, and implement Generative AI solutions, including applications leveraging Retrieval-Augmented Generation (RAG) techniques. Fine-tune existing Large Language Models (LLMs) and potentially develop smaller, specialized language models (SLMs) for specific tasks. Manage the end-to-end lifecycle of AI model development, including data curation, feature extraction, model training, validation, deployment, and monitoring. Research and experiment with state-of-the-art AI/ML/DL techniques to enhance model performance and capabilities. Build and maintain scalable production pipelines for AI models. Collaborate with data engineering and IT teams to define deployment roadmaps and integrate AI solutions into existing systems. Develop AI-powered tools to solve business problems, such as summarization, chatbots, recommendation systems, or code assistance. Stay updated with the latest advancements in Generative AI, machine learning, and deep learning. Qualifications: Proven experience as a Data Scientist, Machine Learning Engineer, or AI Engineer with a focus on LLMs and Generative AI. Strong experience with Generative AI techniques and frameworks (e.g., RAG, Fine-tuning, Langchain, LlamaIndex, PEFT, LoRA). Solid foundation in machine learning (e.g., Regression, Classification, Clustering, XGBoost, SVM) and deep learning (e.g., ANN, LSTM, RNN, CNN) concepts and applications. Proficiency in Python and relevant libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch). Experience with data science principles, including statistics, hypothesis testing, and A/B testing. Experience deploying and managing models in production environments (e.g., using platforms like AWS, Databricks, MLFlow). Familiarity with data handling and processing tools (e.g., SQL, Spark/PySpark). Basic understanding of software engineering practices, including version control (Git) and containerization (Docker). Bachelor's or master’s degree in computer science, Artificial Intelligence, Data Science, or a related quantitative field. Preferred Skills: Experience building RAG-based chatbots or similar applications. Experience developing custom SLMs. Experience with MLOps principles and tools (e.g., MLFlow, Airflow). Experience migrating ML workflows between cloud platforms. Familiarity with vector databases and indexing techniques. Experience with Python web frameworks (e.g., Django, Flask). Experience building and integrating APIs (e.g., RESTful APIs). Basic experience with front-end development or UI building for showcasing AI applications. Qualifications Bachelorʼs or Masterʼs degree in Computer Science, Engineering, or a related discipline.

Company: Coderz Vision Technology Experience: 2–4 years Location: Chennai 📄 About Us Coderz Vision Technology is a leading IT solutions company specializing in software development, emerging technologies, and AI-driven innovation. Our team is passionate about leveraging the latest advancements in machine learning, deep learning, and AI to create cutting-edge solutions for global clients across industries. 🎯 Role Overview We are looking for a talented AI Engineer with 2–3 years of hands-on experience to join our dynamic team. In this role, you’ll design and implement AI models, build intelligent algorithms, and contribute to research and production-grade AI/ML solutions. 🔑 Key Responsibilities Develop, train, and fine-tune machine learning and deep learning models for computer vision, NLP, predictive analytics, and other AI domains. Implement AI algorithms in Python and deploy them into scalable environments. Work closely with data engineering and software teams to integrate AI models into existing products. Preprocess, clean, and analyze structured and unstructured data for model training. Evaluate model performance and optimize for accuracy, scalability, and performance. Conduct literature reviews to stay updated on AI research trends and innovations. Document processes, present findings, and collaborate with cross-functional teams. ✅ Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field. 2–3 years of hands-on experience in AI/ML engineering roles. Strong proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn, etc.). Experience with data preprocessing, feature engineering, and model evaluation techniques. Familiarity with neural networks, NLP, computer vision, and generative AI is a plus. Exposure to cloud platforms (AWS/Azure/GCP) for AI model deployment is a bonus. Excellent problem-solving skills and passion for innovation. 🎯 Why Join Us? Opportunity to work on cutting-edge AI projects with global impact. Collaborative, growth-driven work culture with exposure to diverse technologies. Competitive compensation and performance-based incentives. Continuous learning, training, and career development support. 📧 How to Apply: If you’re interested in joining a forward-thinking team and making a real-world impact with AI, please send your resume and portfolio to hr@coderzvision.com.

NOTE: Timings: 4-6 hours overlap with GMT (Arabian Standard Time) AI Engineer Experience – 5-8 years Contract Duration – 6 months (extendable) Open for Contract Hiring Budget – 1 LPM fixed Location – Remote Must-Have Skills (5–8 Years): Programming – Python (preferred), Java, or C++. Machine Learning – Supervised, unsupervised, and reinforcement learning. Deep Learning – TensorFlow, PyTorch, Keras. Data Handling – Pandas, NumPy, OpenCV, data preprocessing. Model Deployment – REST APIs, Flask/FastAPI, Docker. Cloud – AWS/GCP/Azure ML services. Soft Skills – Analytical thinking, collaboration, communication.

Sinclus Engineering & Consulting Pvt Ltd are Mumbai based Staffing Services Provider to its domestic Clients since 2004. One of our clients at Numaligarh, Golaghat Assam requires following Position for their Projects. Position: Procurement Specialist . Location: Numaligarh, Golaghat Assam. Qualifications Required: Applicant should be First Class M. Com / MBA (Supply Chain Management) / B.E or B. Tech in any Engineering stream. Experience Required: Minimum 03 years of experience in public procurement in tendering activities, bid evaluation, and contract finalization for Govt/PSU. Carry out end-to-end procurement processes for the PSU, including tendering, bid evaluation, and contract finalization. Expertise in procurement regulations i.e. GFR (General Financial Rules) / Public Procurement Guidelines. Hands on experience in AI/ML frameworks i.e. Python, TensorFlow or procurement software i.e. GeM portal or SAP. If your profile matches the required skills and are willing to work at Numaligarh, Golaghat, submit your CV to sin7@sinclus.com Thanks Team Sinclus Follow us on - Website |Facebook| Mobile App | LinkedIn | You tube | WhatsApp | Instagram

Key Responsibilities Architect, build, and deploy AI/ML models for SaaS products at scale. Lead the end-to-end lifecycle of AI projects from data exploration, model development, validation, and deployment, to monitoring and maintenance. Collaborate with Product Management, Engineering, and Design teams to integrate AI capabilities into product offerings. Implement and optimize Retrieval-Augmented Generation (RAG) systems, Large Language Models (LLMs), and other emerging AI/ML techniques. Define and uphold best practices in AI model development, MLOps, and scalable deployment. Mentor and guide a team of AI/ML engineers, setting technical direction and fostering a culture of innovation and excellence. Partner with stakeholders to define AI strategies aligned with overall technology roadmaps and business objectives. Stay abreast of advancements in AI and contribute thought leadership internally and externally. Required Skills & Experience 10-12 years of experience in AI/ML engineering, with a strong record of working in SaaS and product-based environments. Expertise in Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, and/or Generative AI. Hands-on experience with frameworks like TensorFlow, PyTorch, Hugging Face Transformers, etc. Solid experience in designing scalable AI architectures and deploying models in production environments (AWS, GCP, Azure, etc.). Strong programming skills in Python; familiarity with other languages like Java, Go, or Scala is a plus. Deep understanding of MLOps, CI/CD for machine learning pipelines, containerization (Docker, Kubernetes). Experience with LLM fine-tuning, prompt engineering, vector databases (e.g., Pinecone, FAISS) is highly desirable. [Non-negotiable Requisite] Has experience is having trained a SLM (or Medium Language Model), for a particular vertical. This includes pre-training and fine-tuning. Strong problem-solving skills and ability to navigate ambiguous technical challenges. Excellent communication, leadership, and stakeholder management skills. Preferred Qualifications Masters or Ph.D. in Computer Science, Machine Learning, Data Science, or a related field. Experience in Go-to-Market Strategy for AI-powered products. Experience integrating AI into customer-facing SaaS products with measurable outcomes. Contributions to open-source AI projects or published research papers Skills: go,tensorflow,ci/cd,generative ai,computer vision,kubernetes,vector databases,llm fine-tuning,mlops,java,python,deep learning,docker,nlp,hugging face transformers,gcp,azure,ai deployment,scala,aws,machine learning,llm,prompt engineering,natural language processing (nlp),ml pipeline,pytorch

NOTE: Timings: 4-6 hours overlap with GMT (Arabian Standard Time) Position 1: MLOps Engineer Experience: 5–8 years Contract Duration: 6 months (extendable) Budget: 1 Lakh / Month fixed Location: Remote Must-Have Skills (5–8 Years): Strong experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker) Proficiency in CI/CD pipeline creation for ML workflows Hands-on experience with containerization tools such as Docker and orchestration using Kubernetes Good understanding of cloud platforms (AWS/GCP/Azure) for deploying and managing ML models Expertise in monitoring, logging, and model versioning Familiarity with data pipeline orchestration tools (Airflow, Prefect, etc.) Strong Python programming skills and experience with ML libraries (scikit-learn, TensorFlow, PyTorch, etc.) Knowledge of model performance tuning and retraining strategies Ability to collaborate closely with Data Scientists, DevOps, and Engineering teams

We are looking for a skilled and driven Machine Learning Engineer with 3+ years of experience to join our core AI development team. The role involves building and optimising machine learning models, developing data pipelines, and contributing to AI-powered features used in financial crime detection, document intelligence, and compliance analytics. This is a high-impact role for someone passionate about applying machine learning in real-world applications and eager to grow in a fast-paced environment. Responsibilities Build, test, and deploy machine learning models for various data-driven use cases Develop scalable data preprocessing and feature engineering pipelines Collaborate with product and engineering teams to integrate AI functionalities into production systems Analyze model performance, run experiments, and fine-tune algorithms for accuracy and speed Contribute to maintaining version-controlled ML workflows and reusable modules Assist in preparing training datasets from structured and unstructured sources Support model monitoring, feedback loop integration, and continuous improvements Technical Skills Required Strong foundation in Python and applied machine learning Experience with one or more ML frameworks such as scikit-learn, TensorFlow, or PyTorch Understanding of supervised, unsupervised, and basic NLP techniques Familiarity with building data pipelines and working with large datasets (Pandas, NumPy, SQL) Exposure to model deployment concepts, APIs, and inference Basic knowledge of Git, Docker, and cloud environments (AWS/GCP/Azure) Preferred (Nice to Have) Experience with document data (PDFs, scanned files) or OCR tools Exposure to transformer-based models or LLMs Familiarity with ML lifecycle tools (MLflow, DVC, Weights & Biases) Prior experience in fintech, risk analysis, or fraud detection systems Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field 3+ years of hands-on experience in ML/AI development roles Compensation & Growth Competitive compensation aligned with industry benchmarks ESOPs and performance bonuses for high performers Exposure to real-world AI use cases with domain experts in fintech, compliance, and GenAI Opportunity to grow into senior research or MLOps roles based on performance and interest

Job Title: Data Scientist Location: Chennai (Work From Office) Experience: 4 - 8 years About Us: At Objectways, we are at the forefront of AI innovation, solving real-world problems using cutting-edge machine learning and reasoning technologies. Our team works on ambitious projects involving agent trajectory prediction, complex reasoning systems, multimodal intelligence, and preference-based learning. We're looking for a talented Data Scientist eager to push the boundaries of applied AI. Role Overview: We are seeking an experienced Data Scientist (minimum 4 years) to work across a diverse range of AI projects, including: Machine Learning model development Agent Trajectory prediction and modeling Complex Reasoning and Decision Systems Preference Ranking & Reinforcement Learning Multimodal Reasoning (Text, Image, Audio) Prompt Validation and Evaluation for LLMs Key Responsibilities: Design and build ML models for structured and unstructured data Conduct agent-based simulations and develop trajectory learning systems Apply preference learning techniques for fine-tuned ranking outcomes Handle multimodal datasets and develop reasoning pipelines across modalities Validate and optimize prompts for large language model performance Translate research into scalable, production-level implementations Collaborate with cross-functional teams (Engineering, Product, Research) Required Qualifications: Minimum 4 years of hands-on experience in Data Science or Machine Learning roles Strong foundation in Python, PyTorch/TensorFlow, scikit-learn, and ML lifecycle tools Proven expertise in one or more: trajectory modeling, preference ranking, or multimodal systems Experience with LLM prompt engineering and evaluation techniques Solid understanding of complex reasoning algorithms, graph-based methods, or causal inference Strong problem-solving, analytical thinking, and communication skills Preferred Skills: Familiarity with tools like LangChain, Hugging Face, or OpenAI APIs Exposure to RLHF (Reinforcement Learning from Human Feedback) or prompt-tuning Experience with deploying ML models in production environments (e.g., using Docker, MLflow) Why Join Us: Work on high-impact, next-generation AI challenges Collaborate with top talent across domains Competitive salary + benefits + learning budget

Key Responsibilities ● Design, build, and maintain scalable infrastructure for training and deploying machine learning models at scale. ● Operationalize ML models, including the "TruValue UAE" AVM and the property recommendation engine, by creating robust, low-latency APIs for production use. ● Develop and manage data pipelines (ETL) to feed our machine learning models with clean, reliable data for both training and real-time inference. ● Implement and manage the MLOps lifecycle, including CI/CD for models, versioning, monitoring for model drift, and automated retraining. ● Optimize the performance of machine learning models for speed and cost-efficiency in a cloud environment. ● Collaborate with backend engineers to seamlessly integrate ML services with the core platform architecture. ● Work with data scientists to understand model requirements and provide engineering expertise to improve model efficacy and feasibility. ● Build the technical backend for the AI-powered chatbot, integrating it with NLP services and the core platform data. Required Skills and Experience ● 3-5+ years of experience in a Software Engineering, Machine Learning Engineering, or related role. ● A Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. ● Strong software engineering fundamentals with expert proficiency in Python. ● Proven experience deploying machine learning models into a production environment on a major cloud platform (AWS, Google Cloud, or Azure). ● Hands-on experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn. ● Experience building and managing data pipelines using tools like Apache Airflow, Kubeflow Pipelines, or cloud-native solutions. ● Collaborate with cross-functional teams to integrate AI solutions into products. ● Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker) and orchestration (Kubernetes). Job Types: Full-time, Permanent Pay: ₹900,000.00 - ₹1,200,000.00 per year Benefits: Paid sick time Provident Fund Schedule: Day shift Fixed shift Work Location: In person

Overview: As a key member of the team, you will be responsible for building and maintaining the infrastructure, tools, and workflows that enable the efficient, reliable, and secure deployment of LLMs in production environments. You will collaborate closely with data scientists, Data Engineers and product teams to ensure seamless integration of AI capabilities into our core systems. Responsibilities: Design and implement scalable model deployment pipelines for LLMs, ensuring high availability and low latency. Build and maintain CI/CD workflows for model training, evaluation, and release. Monitor and optimize model performance, drift, and resource utilization in production. Manage cloud infrastructure (e.g., AWS, GCP, Azure) and container orchestration (e.g., Kubernetes, Docker) for AI workloads. Implement observability tools to track system health, token usage, and user feedback loops. Ensure security, compliance, and governance of AI systems, including access control and audit logging. Collaborate with cross-functional teams to align infrastructure with product goals and user needs. Stay current with the latest in MLOps and GenAI tooling and drive continuous improvement in deployment practices. Define and evolve the architecture for GenAI systems, ensuring alignment with business goals and scalability requirements Qualifications: Bachelor’s or master’s degree in computer science, Software Engineering, Data Science, or a related technical field. 5 to 7 years of experience in software engineering, DevOps, and 3+ years in machine learning infrastructure roles. Hands-on experience deploying and maintaining machine learning models in production, ideally including LLMs or other deep learning models. Proven experience with cloud platforms (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes). Strong programming skills in Python, with experience in ML libraries (e.g., TensorFlow, PyTorch, Hugging Face). Proficiency in CI/CD pipelines for ML workflows Experience with MLOps tools: MLflow, Kubeflow, DVC, Airflow, Weights & Biases. Knowledge of monitoring and observability tools

Artificial Intelligence / Machine Learning WorkMode :Hybrid Work Location : Chennai / Hyderabad / Work Timing : 2 PM to 11 PM Primary : Artificial Intelligence Job Summary We are seeking a visionary and technically skilled AI Lead to drive the adoption and development of Artificial Intelligence solutions in the financial services domain. This role will lead the design, development, and implementation of machine learning (ML), deep learning (DL), generative AI and Agent AI solutions that improve decision-making, enhance risk management, and deliver intelligent automation across business functions. The ideal candidate combines deep technical expertise in AI with a strong understanding of financial products, regulatory constraints, and business operations. Lead the development of AI/ML strategies aligned with business goals in areas like credit risk, fraud detection, customer insights, algorithmic trading, and compliance automation. Identify AI opportunities within financial products and services and build a roadmap to deliver value. Develop and deploy predictive models for credit scoring, risk analytics, customer segmentation, and forecasting. Implement NLP-based solutions for document processing, sentiment analysis, chatbots, and regulatory reporting. Use advanced AI techniques including deep learning, reinforcement learning, and LLMs to build next-gen financial intelligence systems. Lead and mentor a team of data scientists and machine learning engineers. Foster collaboration with internal stakeholders including product, compliance, and IT. Drive innovation by staying ahead of industry trends in AI, FinTech, and RegTech. Explore and prototype generative AI/Agent AI use cases for financial advisors, reporting automation, or intelligent document analysis. Bachelors or Masters Degree in Computer Science, Statistics, Machine Learning, or related field. Hands-on experience in building and deploying Generative AI models and Agent AI systems. 7+ years of experience in AI/ML, with at least 2 years in a leadership role. Deep understanding of supervised and unsupervised learning, NLP, time-series modeling, and deep learning. Strong programming skills in Python and experience with ML libraries (TensorFlow, PyTorch, Scikit-learn, XGBoost). Experience working with financial datasets (e.g., transaction data, market data, customer data). Hands-on experience with MLOps and deploying models into production environments (e.g., using AWS, Azure ML, or GCP). Secondary Skills Experience with financial risk modeling, credit scoring systems, or fraud detection engines. Familiarity with tools like Snowflake, Databricks, SAS, Bloomberg, or FICO. Knowledge of financial regulatory requirements and risk frameworks. Experience integrating AI solutions into financial workflows or trading systems. Published work or patents in financial AI or applied machine learning.