23 Ml Libraries Jobs

The Forward Deployed Engineer (FDE) - AI Enablement is a senior-level position where you will be responsible for achieving results through solutioning, developing, and implementing AI/ML capabilities as an individual contributor. As an FDE - AI Enablement, you are expected to stay updated on the latest developments in Citi and your field, contributing to the directional strategy by identifying applications within your organization and the business. Your key responsibilities will include enhancing the current toolset with AI/ML capabilities, solutioning for identified use cases, building quick proof-of-concept to showcase solutions, collaborating with the larger AI/ML stream across the data organization, and utilizing your in-depth knowledge and skills across multiple Applications Development areas to provide technical oversight across systems and applications. Additionally, you will be involved in formulating strategies for applications development and other functional areas, gaining comprehensive knowledge of how different business areas integrate to achieve business objectives, and providing evaluative judgment based on the analysis of factual data in complex and unique situations. To be successful in this role, you should have at least 10 years of experience in AI/ML, preferably within the financial industry. Hands-on experience in Python and utilizing ML Libraries such as TensorFlow, Scikit-learn, and Pytorch for Big Data is required. You should also have practical experience with LLMs and GenAI APIs (such as OpenAI GPT, Bard, etc.), applying Machine Learning or NLP models in real-time applications for large datasets, working with MLOPs and Model Deployment Pipelines, using PySpark and understanding big data concepts. Knowledge in Azure OpenAI, Google Vertex, and Stellar is considered a plus. Stakeholder management experience, demonstrated leadership skills, and proven project management skills are also essential for this role. A Bachelor's/University degree is required, with a Master's degree being preferred. This position falls under the Technology job family group and specifically in the Applications Support job family. It is a full-time role. If you require a reasonable accommodation due to a disability to use our search tools or apply for a career opportunity, please review the Accessibility at Citi information. For more details on Citis EEO Policy Statement and the Know Your Rights poster, please refer to the respective documents.,

You should have at least 2-7 years of experience in software engineering and ML development. Proficiency in Python and ML libraries like Scikit-learn, TensorFlow, or PyTorch is essential. Your responsibilities will include building and evaluating models, data preprocessing, and feature engineering. It is important to have a good understanding of REST APIs, Docker, Git, and CI/CD tools. A strong foundation in software engineering principles such as data structures, algorithms, and design patterns is required. Hands-on experience with MLOps platforms like MLflow, TFX, Airflow, and Kubeflow is preferred. Exposure to NLP, large language models (LLMs), or computer vision projects will be beneficial for this role. Experience with cloud platforms such as AWS, GCP, and Azure, as well as managed ML services, is a plus. Any contributions to open-source ML libraries or participation in ML competitions like Kaggle or DrivenData will be considered an advantage.,

As an AI / ML Engineer, you will be responsible for utilizing your expertise in the field of Artificial Intelligence and Machine Learning to develop innovative solutions. You should hold a Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI/ML, Mathematics, or a related field. With a minimum of 6 years of experience in AI/ML, you are expected to demonstrate proficiency in Python and various ML libraries such as scikit-learn, XGBoost, pandas, NumPy, matplotlib, and seaborn. In this role, you will need a strong understanding of machine learning algorithms and deep learning architectures including CNNs, RNNs, and Transformers. Hands-on experience with TensorFlow, PyTorch, or Keras is essential. You should also have expertise in data preprocessing, feature selection, exploratory data analysis (EDA), and model interpretability. Additionally, familiarity with API development and deploying models using frameworks like Flask, FastAPI, or similar tools is required. Experience with MLOps tools such as MLflow, Kubeflow, DVC, and Airflow will be beneficial. Knowledge of cloud platforms like AWS (SageMaker, S3, Lambda), GCP (Vertex AI), or Azure ML is preferred. Proficiency in version control using Git, CI/CD processes, and containerization with Docker is essential for this role. Bonus skills that would be advantageous include familiarity with NLP frameworks (e.g., spaCy, NLTK, Hugging Face Transformers), Computer Vision experience using OpenCV or YOLO/Detectron, and knowledge of Reinforcement Learning or Generative AI (GANs, LLMs). Experience with vector databases such as Pinecone or Weaviate, as well as LangChain for AI agent building, is a plus. Familiarity with data labeling platforms and annotation workflows will also be beneficial. In addition to technical skills, you should possess soft skills such as an analytical mindset, strong problem-solving abilities, effective communication, and collaboration skills. The ability to work independently in a fast-paced, agile environment is crucial. A passion for AI/ML and a proactive approach to staying updated with the latest developments in the field are highly desirable for this role.,

As a seasoned leader in the field of Data, AI, and Automation, you will be responsible for packaging business solutions with clear ROI and effectively communicating the benefits to customers. You will play a crucial role in managing the P&L of the practice, leading a team of Architects, Technical Leads, and Engineers, and ensuring the smooth functioning of the entire team. Your ability to create and nurture a high-performing engineering team will be paramount, as you define and execute the organization's vision to be a leader in the Data, AI, and Automation space. You will set KPIs and objectives for the team that align with the organizational goals, and oversee the efficient allocation of personnel across various engagements. In this role, you will be required to design, architect, and implement cutting-edge Data & AI ML solutions and architectures, while adhering to best practices and principles. Your expertise will be utilized to lead initiatives, provide technical guidance, and drive business development in the realm of Data Science, AI, and ML. Additionally, you will be expected to stay abreast of emerging trends and best practices in Data AI and Automation, and leverage your expertise to lead and grow a superior organization of technical talent. Collaborating with peer engineering teams, you will gather technical requirements to shape Data, AI, and Automation technology roadmaps. Your responsibilities will also include enabling sales strategies with Data & AI solutions, representing the company in industry events, nurturing alliances and partnerships, and developing practice branding artifacts that showcase thought leadership. **Mandatory Qualifications:** - Possess over 15 years of experience in working on highly distributed and scalable enterprise applications - Demonstrate a deep understanding of Data warehouses, Big Data, AI ML, and Automation technologies with over 10 years of experience - Knowledge in Generative AI is desirable - Hands-on experience in developing and implementing machine learning algorithms, utilizing relevant programming languages and big data tools - Proficiency in evaluating and selecting algorithms and tools for projects - Extensive experience in advanced ML techniques such as neural networks, deep learning, and reinforcement learning - Familiarity with open-source technologies, ML libraries, and programming languages - Strong understanding of cloud platforms and their services for implementing Big Data and AI ML solutions - Appreciation of CI/CD processes and tools, guiding the team in decision-making related to CI/CD strategies - Experience with Agile development management tools and API/Microservices architecture-based systems development - Excellent communication, leadership, and interpersonal skills - Strong solutioning and presentation skills - Previous experience in Presales and Enterprise systems integration - Ability to envision and develop innovative solutions and accelerators,

You will be working as a Machine Learning Intern for a duration of 6 months with a stipend of 20k per month. The internship involves a hybrid mode of working, with 3 days in the office and 2 days working from home. Your primary responsibilities will include designing and implementing cutting-edge machine learning models for complex tabular and time series data problems. Additionally, you will be tasked with developing innovative feature engineering techniques to maximize the value extracted from datasets. Researching and applying state-of-the-art algorithms in areas like automated machine learning (AutoML) and neural architecture search will also be part of your role. Furthermore, you will optimize models for performance and scalability in resource-constrained environments, contribute to the development of the company's core ML infrastructure and pipelines, and collaborate on end-to-end ML projects from problem definition to deployment and monitoring. Your involvement in strategic discussions to identify new opportunities for ML applications within the business and conducting independent research to stay updated on the latest ML advancements for tabular and time series data will be crucial. To excel in this role, you should possess a strong theoretical understanding of machine learning concepts, statistical modeling, and optimization techniques. Proven experience in developing and deploying ML models for tabular and time series data, along with advanced programming skills in Python and expertise in ML libraries and frameworks, is essential. Proficiency in working with large-scale datasets and distributed computing environments, as well as experience with modern ML techniques such as gradient boosting, neural networks, and ensemble methods, are also required. Preferred qualifications include contributions to open-source ML projects or research publications, as well as experience with cloud-native ML development and deployment. This internship offers a unique opportunity to work on cutting-edge AI and blockchain intersection projects, contributing to the company's growth and innovation in the field of machine learning.,

As an IoT & AI Intern at Bharat Ecolabs, you will have the opportunity to support the development and integration of sensor networks, data pipelines, and AI models for our smart, modular Packaged Sewage Treatment Plants (STPs). Working out of the NASSCOM Center of Excellence for IoT & AI in Gurugram, you will collaborate closely with our core engineering team. Your key responsibilities will include assisting in the design and development of IoT-enabled sensor and control systems for STPs, building and testing data acquisition modules using sensors for various parameters, developing cloud-based or edge data pipelines for real-time monitoring, and supporting the development of AI/ML models for fault detection and efficiency optimization. Additionally, you will contribute to the creation of dashboards or mobile interfaces for STP data visualization and alerts, as well as conduct testing and debugging of IoT prototypes on pilot installations. The ideal candidate for this role would be a final year student or recent graduate in Electronics, Computer Science, AI, Mechatronics, or related fields with hands-on experience in microcontrollers like Arduino, ESP32, or Raspberry Pi. You should also have familiarity with sensor integration, basic electronics, and communication protocols such as MQTT, Modbus, or LoRa. Proficiency in Python, basic ML libraries like scikit-learn or TensorFlow, and cloud platforms like AWS, Azure, or GCP is desired. Strong problem-solving skills and a passion for applying technology in real-world clean tech solutions are essential for success in this role. Joining us as an IoT & AI Intern at Bharat Ecolabs will provide you with real-world exposure to applied IoT and AI in environmental engineering, mentorship from a passionate founding team, and access to the NASSCOM CoE ecosystem. Upon successful completion of the internship, you will receive a formal Experience Certificate, and there is a possibility to convert the internship into a full-time role based on performance and mutual interest.,

Automation Anywhere is a leader in AI-powered process automation, utilizing AI technologies to drive productivity and innovation across organizations. The company's Automation Success Platform offers a comprehensive suite of solutions including process discovery, RPA, end-to-end process orchestration, document processing, and analytics, all with a security and governance-first approach. By empowering organizations globally, Automation Anywhere aims to unleash productivity gains, drive innovation, enhance customer service, and accelerate business growth. Guided by the vision to enable the future of work through AI-powered automation, the company is committed to unleashing human potential. Learn more at www.automationanywhere.com. Qualifications: - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. - 6 to 12 years of relevant experience. - Proven track record as a Solution Architect or Lead, focusing on integrating Generative AI or exposure to Machine Learning. - Expertise in at least one RPA tool such as Automation Anywhere, UiPath, Blue Prism, Power Automate, and proficiency in programming languages like Python or Java. Skills: - Proficiency in Python or Java for programming and architecture. - Strong analytical and problem-solving skills to translate business requirements into technical solutions. - Experience with statistical packages and machine learning libraries (e.g., R, Python scikit-learn, Spark MLlib). - Familiarity with RDBMS, NoSQL, and Cloud Platforms like AWS/AZURE/GCP. - Knowledge of ethical considerations and data privacy principles related to Generative AI for responsible integration within RPA solutions. - Experience in process analysis, technical documentation, and workflow diagramming. - Designing and implementing scalable, optimized, and secure automation solutions for enterprise-level AI applications. - Expertise in Generative AI technologies such as RAG, LLM, and AI Agent. - Advanced Python programming skills with specialization in Deep Learning frameworks, ML libraries, NLP libraries, and LLM frameworks. Responsibilities: - Lead the design and architecture of complex RPA solutions incorporating Generative AI technologies. - Collaborate with stakeholders to align automation strategies with organizational goals. - Develop high-level and detailed solution designs meeting scalability, reliability, and security standards. - Take technical ownership of end-to-end engagements and mentor a team of senior developers. - Assess the applicability of Generative AI algorithms to optimize automation outcomes. - Stay updated on emerging technologies, particularly in Generative AI, to evaluate their impact on RPA strategies. - Demonstrate adaptability, flexibility, and willingness to work from client locations or office environments as needed. Kindly note that all unsolicited resumes submitted to any @automationanywhere.com email address will not be eligible for an agency fee.,

As a Data Engineering Specialist, you will be responsible for assessing, capturing, and translating complex business issues into structured technical tasks for the data engineering team. This includes designing, building, launching, optimizing, and extending full-stack data and business intelligence solutions. Your role will involve supporting the build of big data environments, focusing on improving data pipelines and data quality, and working with stakeholders to meet business needs. You will create data access tools for the analytics and data scientist team, conduct code reviews, assist other developers, and train team members as required. Additionally, you will ensure that developed systems comply with industry standards and best practices while meeting project requirements. To excel in this role, you should possess a Bachelor's degree in computer science engineering or equivalent, or relevant experience. Certification in cloud technologies, especially Azure, would be beneficial. You should have 2-3+ years of development experience in building and maintaining ETL/ELT pipelines on various sources and operational programming tasks. Experience with Apache data projects or cloud platform equivalents and proficiency in programming languages like Python, Scala, R, Java, Golang, Kotlin, C, or C++ is required. Your work will involve collaborating closely with data scientists, machine learning engineers, and stakeholders to understand requirements and develop data-driven solutions. Troubleshooting, debugging, and resolving issues within generative AI system development, as well as documenting processes, specifications, and training procedures will be part of your responsibilities. In summary, this role requires a strong background in data engineering, proficiency in cloud technologies, experience with data projects and programming languages, and the ability to collaborate effectively with various stakeholders to deliver high-quality data solutions.,

You should have a minimum of 7+ years of professional experience in business analysis, requirement gathering, and solution workflow design for AI/ML/Analytics projects. Proficiency in Python and SQL is required along with a strong understanding of ML libraries and applications such as Time series analysis, Neural Networks, SVMs, boosting methods, and implementation experience in Python. Experience with deep learning techniques is also necessary. Excellent communication skills are essential to effectively collaborate with business SMEs and UX teams. Intermediate knowledge of DevOps practices including CICD, Automation, Build Management, and Versioning is expected. Understanding of Cloud services like Microsoft Azure, GCP, or AWS is a plus. Experience in LLM/Gen AI Prompt Engineering, RAG, and parameter hyper-tuning, as well as in Pyspark, is advantageous. Your responsibilities will include strong problem-solving, critical, and analytical thinking skills with hands-on coding expertise. Proficiency in data fetch, data merge, data wrangling, exploratory data analysis, and feature engineering is required. You should have practical knowledge of machine learning algorithms and be able to drive client engagement while aligning the development team with a technical roadmap. You will implement analytical requirements by defining and analyzing system problems, designing and testing standards and solutions. It is important to develop solutions by preparing and evaluating alternative workflow solutions and design new analytical solutions by analyzing requirements, constructing workflow charts/diagrams, studying system capabilities, and writing specifications. Recommend controls by identifying problems and writing improved procedures and define project requirements by identifying milestones, phases, and elements, forming a project team, and establishing the project budget. Additionally, you will monitor project progress by tracking activity, resolving issues, publishing progress reports, and recommending actions. Maintain system protocols by writing and updating procedures, provide user references by writing and maintaining user documentation, providing help desk support, and training users. Prepare technical reports by collecting, analyzing, and summarizing information and trends, and maintain professional and technical knowledge by attending educational workshops, reviewing professional publications, establishing personal networks, benchmarking state-of-the-art practices, and participating in professional societies. Skills required for this position include Artificial Intelligence, Machine Learning, and AWS. About UST: UST is a global digital transformation solutions provider that has been working with the world's best companies for over 20 years. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients" organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact, touching billions of lives in the process.,

Amity University Online, a leader in digital education with 1,60,000+ learners, is expanding its academic team for AI & Machine Learning programs. We invite experienced and passionate AI/ML professionals to join us in shaping next-gen tech talent. POSITIONS OPEN • PROFESSOR • ASSOCIATE PROFESSOR • ASSISTANT PROFESSOR • VISITING FACULTY • PROFESSOR OF PRACTICE ELIGIBILITY ACADEMIC QUALIFICATIONS • Masters degree in Computer Science, Engineering, Data Science, or related fields. • Ph.D. holders or research scholars in AI/ML are strongly encouraged to apply. TECHNICAL EXPERTISE • Proficiency in Python and ML libraries (TensorFlow, PyTorch, Keras, Scikit-learn) • Expertise in Supervised & Unsupervised Learning, Neural Networks, NLP, and Computer Vision • Familiarity with cloud platforms (AWS, Azure, GCP) is an added advantage EXPERIENCE • Minimum 2 years in teaching and/or industry AI/ML roles • Demonstrated success in training delivery or AI/ML project execution PREFERRED CERTIFICATIONS • AI/ML Certification • Other relevant certifications ROLE RESPONSIBILITIES • Deliver engaging and up-to-date AI/ML sessions (Online/Offline) • Mentor learners through real-world projects and capstone assignments • Contribute to curriculum design, content development, and assessments • Stay updated with evolving AI/ML trends and industry practices To apply, email your updated CV to hr@amityonline.com

About Apexon: Apexon is a digital-first technology services firm specializing in accelerating business transformation and delivering human-centric digital experiences. We have been meeting customers wherever they are in the digital lifecycle and helping them outperform their competition through speed and innovation.Apexon brings together distinct core competencies in AI, analytics, app development, cloud, commerce, CX, data, DevOps, IoT, mobile, quality engineering and UX, and our deep expertise in BFSI, healthcare, and life sciences – to help businesses capitalize on the unlimited opportunities digital offers. Our reputation is built on a comprehensive suite of engineering services, a dedication to solving clients’ toughest technology problems, and a commitment to continuous improvement. Backed by Goldman Sachs Asset Management and Everstone Capital, Apexon now has a global presence of 15 offices (and 10 delivery centers) across four continents. We enable #HumanFirstDigital Key Responsibilities: Design, develop, and maintain CI/CD pipelines for ML models and data workflows. Collaborate with data science teams to productionize models using tools like MLflow, Kubeflow, or SageMaker. Automate training, validation, testing, and deployment of machine learning models. Monitor model performance, drift, and retraining needs. Ensure version control of datasets, code, and model artifacts. Implement model governance, audit trails, and reproducibility. Optimize model serving infrastructure (REST APIs, batch/streaming inference). Integrate ML solutions with cloud services (AWS, Azure, GCP). Ensure security, compliance, and reliability of ML systems. Required Skills and Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field. 4+ years of experience in MLOps, DevOps, or ML engineering roles. Strong experience with ML pipeline tools (MLflow, Kubeflow, TFX, SageMaker Pipelines). Proficiency in containerization and orchestration tools (Docker, Kubernetes, Airflow). Strong Python coding skills and familiarity with ML libraries (scikit-learn, TensorFlow, PyTorch). Experience with cloud platforms (AWS, Azure, GCP) and their ML services. Knowledge of CI/CD tools (GitLab CI/CD, Jenkins, GitHub Actions). Familiarity with monitoring/logging tools (Prometheus, Grafana, ELK, Sentry). Understanding of data versioning (DVC, LakeFS) and feature stores (Feast, Tecton). Strong grasp of model testing, validation, and monitoring in production environments. Our Commitment to Diversity & Inclusion: Did you know that Apexon has been Certified™ by Great Place To Work®, the global authority on workplace culture, in each of the three regions in which it operates: USA (for the fourth time in 2023), India (seven consecutive certifications as of 2023), and the UK.Apexon is committed to being an equal opportunity employer and promoting diversity in the workplace. We take affirmative action to ensure equal employment opportunity for all qualified individuals. Apexon strictly prohibits discrimination and harassment of any kind and provides equal employment opportunities to employees and applicants without regard to gender, race, color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. You can read about our Job Applicant Privacy policy here Job Applicant Privacy Policy (apexon.com) Our Perks and Benefits: Our benefits and rewards program has been thoughtfully designed to recognize your skills and contributions, elevate your learning/upskilling experience and provide care and support for you and your loved ones. As an Apexon Associate, you get continuous skill-based development, opportunities for career advancement, and access to comprehensive health and well-being benefits and assistance. We also offer: Group Health Insurance covering family of 4 Term Insurance and Accident Insurance Paid Holidays & Earned Leaves Paid Parental LeaveoLearning & Career Development Employee Wellness

You should have a minimum of 7+ years of professional experience in business analysis, requirement gathering, and solution workflow design for AI/ML/Analytics projects. Your programming skills should include proficiency in Python and SQL. You must have a strong understanding of ML libraries and applications such as Time series analysis, Neural Networks, SVMs, boosting methods, with implementation experience in Python. Experience with deep learning techniques is required. Excellent communication skills are essential to collaborate effectively with business SMEs and UX teams. You should also have intermediate knowledge of DevOps practices, including CICD, Automation, Build Management, and Versioning. Understanding of Cloud services like Microsoft Azure, GCP, or AWS is necessary. Experience in LLM/Gen AI Prompt Engineering, RAG, and parameter hyper-tuning, as well as Pyspark, will be advantageous. Your responsibilities will include strong problem-solving, critical, and analytical thinking skills with hands-on coding expertise. Proficiency in data fetch, data merge, data wrangling, exploratory data analysis, and feature engineering is required. You will need practical knowledge of machine learning algorithms, drive client engagement, and align the development team with a technical roadmap. Implementing analytical requirements, defining and analyzing system problems, designing, and testing standards and solutions are part of your responsibilities. Furthermore, you will design new analytical solutions, study business functions, and determine operational objectives. Recommending controls, defining project requirements, monitoring project progress, maintaining system protocols, providing user references, maintaining user confidence, preparing technical reports, and staying updated with professional and technical knowledge are also essential tasks. Skills required for this role include Artificial Intelligence, Machine Learning, and AWS. About UST: UST is a global digital transformation solutions provider that partners with clients to make a real impact through transformation. With over 30,000 employees in 30 countries, UST embeds innovation and agility into their clients" organizations, touching billions of lives in the process.,

About the Role: We are looking for a highly skilled and motivated Data Scientist with 35 years of experience to join our Data Innovation team. The ideal candidate will have strong analytical skills, hands-on experience in Computer Vision and Large Language Models (LLMs), and a proven track record of turning complex data into actionable insights and intelligent solutions. This role will involve working on high-impact AI solutions for unstructured data, including images and documents. Designation – Data Scientist Key Responsibilities: Design, develop, and deploy models for computer vision tasks such as object detection, image classification, OCR, segmentation, etc. Build and fine-tune LLM-based pipelines for tasks such as information extraction, document summarization, chat-based interfaces, and automated reasoning. Work closely with cross-functional teams (engineering, product, business) to translate business problems into data science solutions. Conduct exploratory data analysis, statistical modelling, and feature engineering across diverse data sources. Evaluate model performance using appropriate metrics and iterate for improvement. Stay up to date with the latest research and advancements in AI/ML, computer vision, and NLP. Required Qualifications: Bachelor’s or master’s degree in computer science, Data Science, Engineering, or related fields. 3–5 years of hands-on experience in Data Science or Machine Learning roles. Strong proficiency in Python and ML libraries such as scikit-learn, pandas, PyTorch/TensorFlow, OpenCV, Langchain etc. Experience with Computer Vision frameworks (e.g., YOLO, Detectron2, MM Detection) and LLMs (e.g., Hugging Face Transformers, Lang Chain, LLaMA, GPT). Experience with real-world model deployment and evaluation. Strong grasp of machine learning concepts, statistical analysis, and data manipulation. Excellent problem-solving, communication, and stakeholder collaboration skills. Good to have: Exposure to the lending, finance, or banking domain (e.g., credit scoring, income estimation, fraud detection). Experience with document AI or multi-modal AI systems. Familiarity with cloud platforms (AWS/GCP/Azure) and MLops tools. Experience working with OCR engines (Tesseract, PaddleOCR, etc.) and integrating CV+LLM pipelines. Understanding of RAG pipelines, fine-tuning of open-source LLMs, or prompt engineering. Location – Ahmedabad (Onsite) Experience – 3 to 5 Years

3-5 years of experience in ML/AI with at least 1 year in GenAI. Proficiency in Python and ML libraries (e.g., Hugging Face, LangChain, OpenAI). Strong skills in building APIs and deploying AI solutions. Experience in data pipeline development.

Job Title: TM-Data Scientist-Audit Innovation & Digital Transformation PURPOSE OF THE JOB To work as a junior data scientist and contribute to development of AI ML, NLP, and Gen AI solutions. Work on diverse projects involving data analysis, predictive modeling, AI/ML and Gen AI implementation while collaborating with cross-functional teams to drive data-driven analytics and decision making. KEY RESPONSIBILITIES Design and deploy machine learning pipelines for production environments Work with NLP techniques for text analysis, sentiment analysis Implement Gen AI solutions to automate content creation and data augmentation Contribute to Video Analytics projects using Computer Vision and Multi-modal LLMs Create clear, compelling data visualizations and dashboards using tools like Power BI or Python Document methodologies, findings, and model performance for reproducibility Present findings and recommendations to both technical and non-technical stakeholders Collaborate with engineers and business analysts to translate business requirements into analytical solutions Stay current with latest developments in AI/ML technologies and best practices Key Skills 1-2 years of hands-on experience in developing data science, AIML, NLP, Computer Vision, Gen AI solutions Proficiency in Python for data analysis and machine learning Experience with ML libraries such as scikit-learn, TensorFlow, PyTorch, or similar frameworks Knowledge of NLP techniques and libraries (NLTK, spaCy, Hugging Face Transformers) Familiarity with generative AI models and their applications SQL proficiency for database querying and data manipulation Experience with data visualization tools and techniques Understanding of statistical concepts Educational Qualifications Bachelors or Masters degree in Computer Science, Engineering, or a related field. Certifications in areas such as Data Engineering, Cloud Skills, AI/ML, Gen AI will be an added advantage. Experience Required 1-2 years of experience in Data Science, AI ML, Gen AI. Job Location- Kanjurmarg, Mumbai.

We are seeking an experienced professional in AI and machine learning with a strong focus on large language models (LLMs) for a 9-month project The role involves hands-on expertise in developing and deploying agentic systems and working with transformer architectures, fine-tuning, prompt engineering, and task adaptation Responsibilities include leveraging reinforcement learning or similar methods for goal-oriented autonomous systems, deploying models using MLOps practices, and managing large datasets in production environments The ideal candidate should excel in Python, ML libraries (Hugging Face Transformers, TensorFlow, PyTorch), data engineering principles, and cloud platforms (AWS, GCP, Azure) Strong analytical and communication skills are essential to solve complex challenges and articulate insights to stakeholders

What you will do Let s do this. Let s change the world. We are seeking a highly skilled Machine Learning Engineer with a strong MLOps background to join our team. You will play a pivotal role in building and scaling our machine learning models from development to production. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines. Roles & Responsibilities: Collaborate with data scientists to develop, train, and evaluate machine learning models. Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring. Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment. Implement DevOps/MLOps best practices to automate ML workflows and improve efficiency. Develop and implement monitoring systems to track model performance and identify issues. Conduct A/B testing and experimentation to optimize model performance. Work closely with data scientists, engineers, and product teams to deliver ML solutions. Guide and mentor junior engineers in the team Stay updated with the latest trends and advancements What we expect of you We are all different, yet we all use our unique contributions to serve patients. Basic Qualifications: Doctorate degree and 2 years of Computer Science, Statistics, and Data Science, Machine Learning experience OR Master s degree and 8 to 10 years of Computer Science, Statistics, and Data Science, Machine Learning experience OR Bachelor s degree and 10 to 14 years of Computer Science, Statistics, and Data Science, Machine Learning experience OR Diploma and 14 to 18 years of years of Computer Science, Statistics, and Data Science, Machine Learning experience Preferred Qualifications: Must-Have Skills: Strong foundation in machine learning algorithms and techniques Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow); Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD) Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn) Outstanding analytical and problem-solving skills; Ability to learn quickly; Excellent communication and interpersonal skills Good-to-Have Skills: Experience with big data technologies (e.g., Spark), and performance tuning in query and data processing Experience with data engineering and pipeline development Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification Knowledge of NLP techniques for text analysis and sentiment analysis Experience in analyzing time-series data for forecasting and trend analysis Familiar with AWS, Azure, or Google Cloud; Familiar with Databricks platform for data analytics and MLOps Professional Certifications Cloud Computing and Databricks certificate preferred Soft Skills: Excellent analytical and fixing skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals Strong presentation and public speaking skills. What you can expect of us As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we ll support your journey every step of the way. In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards.

We are seeking a skilled and innovative AI/ML Engineer to design, develop, and implement machine learning models and artificial intelligence solutions that drive business impact. The ideal candidate will have strong experience in data science, statistical modeling, and deep learning frameworks, along with the ability to work in cross-functional teams. Build and deploy scalable ML models for classification, regression, recommendation, or NLP tasks. Collect, clean, and preprocess large datasets from various sources. Design and run experiments to evaluate model performance and improve accuracy. Collaborate with software engineers to integrate models into production systems. Stay updated with the latest AI/ML research and technologies to apply best practices. Optimize model performance and ensure alignment with business goals.

Data Analytics Engineer / Data Scientist Location- Mysuru (Preferred) or Remote (India) Full-Time | 3+ Years Experience ABOUT HOPTEKAI: At Hoptek, a Kearney Company, were building AI-powered SaaS products that help trucking companies operate smarter from pricing freight and planning networks to allocating assets and reducing waste. We’re looking for a Data Analytics Engineer / Data Scientist who’s excited to solve hard operations problems, build AI models that get embedded into our products, and help our customers get smarter through data. If you love building applied ML solutions and developing new ideas at the intersection of logistics and optimization, this role is for you. POSITION OVERVIEW: Build machine learning and optimization models to support pricing, routing, and network planning Partner with product and engineering teams to embed AI algorithms into customer-facing software Analyze freight networks and develop insights that drive operational efficiency Use PostgreSQL and Apache Superset to develop internal and customer-facing analytics as needed Prototype innovative solutions to unstructured problems using Python, OR techniques, and statistical methods Understand how customers interact with the platform and develop analytics to support adoption and value delivery What We’re Looking For: 3+ years of experience in data science, analytics engineering, or operations research Proficiency in Python, SQL, and relevant data/ML libraries (e.g., pandas, scikit-learn, XGBoost) Strong grasp of optimization techniques, network models, or decision science Familiarity with data visualization tools — especially Apache Superset Ability to work with real-world, messy logistics data and extract actionable intelligence Curiosity and creativity in approaching open-ended product and analytics challenges Bonus Points For: Experience in transportation, logistics, or freight planning Hands-on experience with graph analytics or geospatial data Experience productionizing ML/OR models within SaaS applications Exposure to pricing algorithms, dynamic optimization, or network simulations Why HOPTEKAI: Applied AI, Real Impact: Your work powers critical product decisions — from what to bid, to where to send the next truck Innovation-Driven: You’ll get to explore new techniques and shape the future of optimization in freight Close Loop from Data to Product: Help us transform ideas into algorithms, and algorithms into product features Mysuru Preferred: Collaborate on-site with our core team — or work remotely within India We’re Hiring Fast: Join a high-impact team at a critical growth moment

AI/ML, AWS-based solutions. Amazon SageMaker, Python and ML libraries, data engineering on AWS, AI/ML algorithms &model deployment strategies.CI/CD, Cloud Formation, Terraform). AWS Certified Machine Learning. generative AI, real-time inference &edge

Data Analytics Engineer / Data Scientist Location- Mysuru (Preferred) or Remote (India) Full-Time | 3+ Years Experience ABOUT KEARNEY: Kearney is a leading global management consulting firm with more than 5,300 people working in more than 40 countries. We work with more than three-quarters of the Fortune Global 500, as well as with the most influential governmental and nonprofit organizations. Kearney is a partner-owned firm with a distinctive, collegial culture that transcends organizational and geographic boundariesand it shows. Regardless of location or rank, our consultants are down to earth, approachable, and have a shared passion for doing innovative client work that provides clear benefits to the organizations we work with in both the short and long term. ABOUT HOPTEKAI: At Hoptek, a Kearney Company, were building AI-powered SaaS products that help trucking companies operate smarter — from pricing freight and planning networks to allocating assets and reducing waste. We’re looking for a Data Analytics Engineer / Data Scientist who’s excited to solve hard operations problems, build AI models that get embedded into our products, and help our customers get smarter through data. If you love building applied ML solutions and developing new ideas at the intersection of logistics and optimization, this role is for you. POSITION OVERVIEW: Build machine learning and optimization models to support pricing, routing, and network planning Partner with product and engineering teams to embed AI algorithms into customer-facing software Analyze freight networks and develop insights that drive operational efficiency Use PostgreSQL and Apache Superset to develop internal and customer-facing analytics as needed Prototype innovative solutions to unstructured problems using Python, OR techniques, and statistical methods Understand how customers interact with the platform and develop analytics to support adoption and value delivery What We’re Looking For: 3+ years of experience in data science, analytics engineering, or operations research Proficiency in Python, SQL, and relevant data/ML libraries (e.g., pandas, scikit-learn, XGBoost) Strong grasp of optimization techniques, network models, or decision science Familiarity with data visualization tools — especially Apache Superset Ability to work with real-world, messy logistics data and extract actionable intelligence Curiosity and creativity in approaching open-ended product and analytics challenges Bonus Points For: Experience in transportation, logistics, or freight planning Hands-on experience with graph analytics or geospatial data Experience productionizing ML/OR models within SaaS applications Exposure to pricing algorithms, dynamic optimization, or network simulations Why Kearney HOPTEKAI: Applied AI, Real Impact: Your work powers critical product decisions — from what to bid, to where to send the next truck Innovation-Driven: You’ll get to explore new techniques and shape the future of optimization in freight Close Loop from Data to Product: Help us transform ideas into algorithms, and algorithms into product features Mysuru Preferred: Collaborate on-site with our core team — or work remotely within India We’re Hiring Fast: Join a high-impact team at a critical growth moment Equal Employment Opportunity and Nondiscrimination HOPTEK, A Kearney Company, prides itself on providing a culture that allows employees to bring their best selves to work every day. Our people can feel comfortable, confident, and joyful to do great things for our firm, our teams, and our clients. HOPTEK, A Kearney Company, aims to build diverse capabilities to help our clients solve their most mission-critical problems. HOPTEK, A Kearney Company, is committed to building a diverse, unbiased, and inclusive workforce. We are an equal opportunity employer; we recruit, hire, train, promote, develop, and provide other conditions of employment without regard to a person’s gender identity or expression, sexual orientation, race, religion, age, national origin, disability, marital status, pregnancy status, veteran status, genetic information, or any other differences consistent with applicable laws. This includes providing reasonable accommodation for disabilities or religious beliefs and practices. Members of communities historically underrepresented in analytics and consulting are encouraged to apply.

We are seeking a skilled and experienced Machine Learning Engineer specialized in Natural Language Processing (NLP) and Computer Vision to join our team. The ideal candidate should have a strong foundation in ML and AI principles, coupled with a proven track record of developing and deploying a minimum of 20+ models in these domains. Role & responsibilities Develop and implement state-of-the-art machine learning algorithms and models for NLP and computer vision applications. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Conduct thorough data analysis, pre-processing, and feature engineering to extract meaningful insights from structured and unstructured data. Design and implement scalable and efficient machine learning pipelines for training, evaluation, and inference. Experiment with various deep learning architectures, hyperparameters, and optimization techniques to improve model performance. Stay updated with the latest advancements in ML and AI research and evaluate their potential applications in our domain. Work closely with software engineers to integrate ML models into production systems and ensure their robustness and scalability. Perform rigorous testing and validation of models to ensure their accuracy, reliability, and generalization capability. Continuously monitor and maintain deployed models, and implement necessary updates and enhancements as required. Document code, methodologies, and findings effectively, and contribute to internal knowledge sharing initiatives Preferred candidate profile Strong theoretical understanding of machine learning algorithms, deep learning frameworks, and statistical modeling techniques. Proficiency in programming languages such as Python, along with experience in popular ML libraries such as TensorFlow, PyTorch, or scikit-learn. Hands-on experience in developing and deploying machine learning models for NLP and computer vision tasks, with a demonstrable portfolio of projects. Solid understanding of natural language processing techniques, including text classification, sentiment analysis, named entity recognition, etc. Familiarity with computer vision concepts such as image classification, object detection, image segmentation, etc., and experience with frameworks like OpenCV or TensorFlow. Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes) is a plus.

Expertise in Python, R, SQL, and common ML libraries (scikit-learn, TensorFlow, PyTorch, XGBoost, etc.). Strong understanding of MLOps, data engineering, and cloud platforms (AWS, GCP, Azure).