8 Ml Libraries Jobs

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).