11 Model Selection Jobs

As a Data Scientist Engineer, your role involves designing scalable machine learning architectures and implementing data science solutions for complex business problems. You will be responsible for key tasks such as model development, data preprocessing, model training, evaluation & optimization, model deployment, cross-functional collaboration, research & innovation, and documentation. Key Responsibilities: - Design and implement machine learning models to address business challenges effectively. - Clean, preprocess, and analyze large-scale datasets for extracting insights and engineering model features. - Train and fine-tune ML models using deep learning, regression, classification, and ensemble techniques. - Evaluate model performance and improve accuracy, efficiency, and scalability. - Deploy ML models into production environments; monitor and retrain models as needed. - Collaborate with engineers, data scientists, and stakeholders to integrate ML solutions. - Stay current with the latest trends in AI/ML and contribute to knowledge sharing. - Maintain thorough documentation of models, workflows, and processes. Qualifications: - Bachelors or Masters degree in Computer Science, Data Science, Machine Learning, or a related field - 6-10 years of industry experience in data science, machine learning, or related domains Must-Have Skills: - Experience in Time Series Forecasting, Regression, and Classification models - Proficient in Python, R, and Data Analysis - Strong experience with Pandas, NumPy, Matplotlib for large data handling - Version control tools like Git - ML Frameworks: TensorFlow, PyTorch, Scikit-learn, Keras - Exposure to Cloud Platforms: AWS / Azure / GCP - Experience with Docker and Kubernetes - Hands-on in Data Collection, Feature Engineering, Model Selection, Evaluation, and Deployment Good to Have: - Exposure to Big Data tools such as Hadoop, Spark - BFSI / Banking domain experience - Familiarity with additional AI/ML libraries and tools beyond the mentioned frameworks In addition to the technical skills required for the role, you should be open to working on a contractual or temporary basis with a contract length of 6 months. You may be based in Noida with the requirement of working from the office twice a week and flexibility for travel as needed.,

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. And we're counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. As an AI Automation Architect for Customer Business Process Manager, you will be responsible for working on end-to-end pipelines, enabling data curation, building and fine-tuning Generative AI models, and deploying them into scalable production streams. This role offers a fantastic opportunity to be part of a leading firm and instrumental in the growth of a new service offering within the Supply Chain Technology group of our GDS consulting Team. You will collaborate with EY Supply Chain & Operations stakeholders and data engineering teams to enable high-quality data curation for model training and evaluation. Design, develop, and fine-tune Generative AI models using frameworks like LangChain, Hugging Face, TensorFlow, or PyTorch. Implement solutions for data pre-processing, tokenization, and dataset augmentation. Deploy Generative AI models on cloud platforms (e.g., AWS, GCP, Azure) or edge devices, ensuring scalability and robustness. Work on MLOps pipelines, including CI/CD workflows, model monitoring, and retraining strategies. Conduct performance benchmarking, hyperparameter tuning, and optimization to improve model efficiency. Stay updated on the latest trends and advancements in Generative AI and integrate best practices into project workflows. To qualify for this role, you must have 6-10 years of experience in ML, MLOps, Generative AI LLMs as a Developer/Lead/Architect. Expertise in Data Engineering, Data transformation, curation, feature selection, ETL Mappings, Data Warehouse concepts. Thorough knowledge in SQL, Python, PySpark, Spark, and other languages. Experience in developing end-to-end GenAI solutions with the capability to migrate the solution for Production. Knowledge of Cloud platforms like Azure, AWS, GCP, etc. Knowledge of frameworks like LangChain, Hugging Face, Azure ML Studio Azure. Knowledge of data modeling and Vector DB management and modeling. Design and develop complex flows and processes. Ideally, you'll also have a good understanding of Customer and Supply Chain processes and operations, strong knowledge of Programming concepts, Cloud Concepts, LLM Models, design, and coding. Experience in data handling to resolve any data issues as per client needs. Experience in designing and developing DB objects and Vector DBs. Experience of creating complex SQL queries, PySpark code, Python Scripting for retrieving, manipulating, checking, and migrating complex datasets. Experience in Model selection and tuning of the model. Good verbal and written communication in English, Strong interpersonal, analytical, and problem-solving abilities. Experience of interacting with customers in understanding business requirement documents and translating them into ETL specifications and High- and Low-level design documents. Candidates having additional knowledge of BI tools such as PowerBi, Tableau, etc will be preferred. Experience with Cloud databases and multiple ETL tools. At EY, you'll have the opportunity to drive Generative AI and ML-related developments, with additional knowledge of data structures, preferably in the Supply Chain Industry. You'll be part of a market-leading, multi-disciplinary team of 10,000+ professionals, working with leading businesses across a range of industries globally. EY offers support, coaching, and feedback from engaging colleagues, opportunities to develop new skills and progress your career, and the freedom and flexibility to handle your role in a way that's right for you. EY exists to build a better working world, helping to create long-term value for clients, people, and society and build trust in the capital markets.,

As a Data Scientist specializing in Generative AI at Aligned Automation, you will play a crucial role in delivering both business and technical services to our clients. With over 11 years of experience in Artificial Intelligence and Big Data, you will leverage your expertise to assist customers in planning and executing their Generative AI initiatives. Your responsibilities will include engaging with C-level customer roles, creating strategic roadmaps, and collaborating with data scientists to explore current and future ecosystems. To excel in this role, you must possess a deep understanding of Generative AI, including model selection, data preparation, model finetuning, and guardrail implementation. Additionally, familiarity with tools such as Kubernetes, MLops, and AIops will be essential. Your ability to build trust with customers, facilitate workshops, and deliver impactful presentations will be key to success. Your experience in conducting architectural analyses, IT engagements, and client interactions will be valuable in providing tailored technology services at an enterprise level. Proficiency in Nvidia AI tools, Large Language Models (LLM), MLOps, AIOps tools, Lean and Iterative Deployment Methodologies, as well as educational background in Machine Learning, will further enhance your capabilities in this role. If you are a candidate who thrives in a customer-facing role, excels in delivering outstanding work products, and is keen on contributing to a more optimistic and better world through technology, we invite you to explore this opportunity further. Join us in our mission to digitize enterprise operations and make a positive global impact.,

We are seeking an AI specialist with over 3 years of experience to develop and implement AI solutions, primarily focusing on Java. The ideal candidate will have a strong proficiency in Java-based AI development, while experience in Python is also valued. In this role, you will be responsible for designing intelligent agents and applying cutting-edge machine learning techniques to address complex business challenges. Your main responsibilities will include designing, building, and deploying AI agents using Java to automate decision-making processes. You will utilize frameworks such as LangChain, LlamaIndex, and other advanced AI frameworks, ensuring smooth integration into Java applications. Additionally, you will work hands-on with machine learning toolkits, leveraging Java-based libraries for AI development. It is essential to have a deep understanding of machine learning concepts and apply them to real-world problems using Java. Furthermore, you will focus on ensuring data and application security in the AI pipeline, as well as leading efforts in model selection, training, and optimization within Java-based frameworks. Thorough evaluation and testing of AI models to ensure effectiveness and scalability in Java-based applications are also key responsibilities. Collaboration with Data Engineers to refine training datasets and contribute to AI/ML operations for deploying and managing models in production environments will be essential. Qualifications for this role include a Bachelor's degree in Engineering, along with at least 3 years of experience as an AI Engineer or similar role. You should have proven experience with AI agents, a strong proficiency in Java for AI development, and familiarity with popular AI frameworks. Experience with machine learning toolkits and a solid understanding of model training, fine-tuning, and evaluation processes within a Java-based environment are also required. Skills in MLOps or AI model deployment and management in Java-based environments are considered a plus. Preferred Skills: - Excellent problem-solving abilities with a focus on innovative AI-driven solutions in Java. - Strong programming skills in Java (required) and Python (preferred). - Familiarity with cloud environments and deploying AI/ML solutions on platforms such as AWS, GCP, or Azure.,

As a Computer Vision Engineer, you will play a crucial role in transforming business challenges into data-driven machine learning solutions. Your primary responsibility will be to design, develop, and implement computer vision algorithms and models for image and video analysis, object detection, recognition, and tracking. Collaborating with cross-functional teams, you will translate business requirements into technical specifications for computer vision solutions. Staying updated with the latest advancements in computer vision and deep learning, you will identify opportunities for innovation and optimization. To excel in this role, you should have at least 2 years of experience in computer vision and/or deep learning for object detection and tracking, as well as semantic or instance segmentation in academic or industrial domains. Proficiency in Python and related packages such as numpy, scikit-image, PIL, opencv, matplotlib, and seaborn is essential. Additionally, you must possess a strong foundation in data structures and algorithms in Python or C++, along with experience in training models through GPU computing using NVIDIA CUDA or on cloud platforms. Your responsibilities will also include working with large datasets, applying data preprocessing techniques, and optimizing computer vision models for efficiency, accuracy, and real-time performance. Hands-on experience with machine/deep learning frameworks like Tensorflow, Keras, and PyTorch is required, along with expertise in identifying data imbalance, data compatibility, data privacy, data normalization, and data encoding issues. You will be involved in model selection, evaluation, training, validation, and testing, exploring different methods and scenarios for effective outcomes. In this role, you will have the opportunity to work in a dynamic environment with a focus on innovation and collaboration. The position offers a 5-day working week with flexible timings. While we are not currently hiring for the Computer Vision Engineer role, please check back later for potential opportunities to join our team.,

As a part-time Data Scientist with over 4 years of experience, you will be responsible for building the Machine Learning foundation for a high-velocity US-focused startup. The position offers approximately 3 months of work initially, with the potential for a full-time role requiring 12 hours per week. It is important to note that Data Analytics is distinguished from Data Science. Inveno, a New York City-based startup, aims to automate the manual resource planning processes that occur daily at warehouses across the United States. The current problem being addressed is the reliance of 75% of US warehouses on manual shift planning, leading to inefficiencies amounting to over $1 million per warehouse annually. By utilizing operational data and developing custom AI and optimization models, Inveno seeks to assist warehouse managers in planning with precision, speed, and scalability. The founding team behind Inveno consists of a warehouse operations expert with 8 years of experience, a CEO with a successful track record of building and exiting companies, and a CTO experienced in scaling engineering and systems across various ventures globally. The company has made significant progress, with the V1 product set to go live with the first client in 2 months. Inveno has also secured a paid contract with a global multi-brand conglomerate and has a promising pipeline with some of the largest retailers in the US. As a Data Scientist in this role, you will be responsible for leading the development of the optimizer, building machine learning models, collaborating on the LLM interaction layer, and establishing MLOps best practices. Key responsibilities include architecting and implementing core optimization engines, creating supervised learning models, designing workflows, and setting up model versioning and deployment pipelines. Qualifications and skills required for this position include experience in designing and deploying constraint-based optimization models, advanced Python skills, a strong foundation in supervised machine learning, the ability to translate complex operational problems into solvable models, and a degree in Computer Science, Operations Research, Statistics, or a related quantitative field.,

As a part-time Data Scientist with more than 4 years of experience, you will have the opportunity to build the machine learning foundation for a high-velocity US-focused startup. The position involves approximately 3 months of work initially, with the potential for full-time engagement (12 hours per week). Inveno, a New York City-based startup, is dedicated to automating the manual resource planning processes that occur daily in US warehouses. The primary problem being addressed is the prevalent manual shift planning in 75% of US warehouses, leading to inefficiencies costing over $1 million annually per warehouse. By leveraging operational data and developing custom AI and optimization models, Inveno aims to empower warehouse managers with precise, efficient, and scalable planning solutions. The founding team of Inveno consists of three members: - A warehouse operations expert with 8 years of experience at prominent logistics startups in the US and India. - A CEO with a track record of building and exiting three companies, as well as leading teams at Alibaba Group. - A CTO experienced in scaling engineering and systems across various international ventures. In terms of progress, Inveno's V1 product is scheduled to go live with the first client within 2 months. The startup has already secured a paid contract with a global multi-brand conglomerate and has a promising pipeline including some of the largest retailers in the US. As a data scientist joining the team, you will play a crucial role in leading the development of the core optimization engine, building machine learning models to support the optimizer, shaping the LLM interaction layer, and establishing MLOps best practices. Key responsibilities include architecting and implementing the core optimization engine, creating and deploying supervised learning models, collaborating with engineering on workflow design, and setting up model versioning, deployment, monitoring, and experimentation pipelines. Qualifications & Skills Required: - Experience in designing and deploying constraint-based optimization models using tools like Google OR-Tools, Gurobi, CPLEX, or similar. - Proficiency in advanced Python skills and familiarity with the data science stack including NumPy, pandas, and scikit-learn. - Strong foundation in supervised machine learning, encompassing feature engineering, model selection, and validation techniques. - Demonstrated ability to translate complex operational problems into solvable mathematical or machine learning models. - Bachelor's or Master's degree in Computer Science, Operations Research, Statistics, or a related quantitative field. Joining Inveno as a Data Scientist presents a significant opportunity for career advancement by taking ownership of the development and deployment of a foundational model that drives innovation in a critical sector.,

You are seeking a Director- AIML position based in Andheri, Mumbai. With 12-16 years of experience, you are a hands-on AI engineer or data scientist who excels in driving impactful AI initiatives in production settings. Your passion lies in solving complex problems, developing scalable systems, and staying updated on the latest AI advancements. Your must-have skills include proven expertise in framing and resolving complex problems using AI models, particularly in computer vision or NLP, and GenAI deployment at scale. You possess hands-on experience with LLMs, specializing in fine-tuning, retrieval-augmented generation (RAG), and model selection. Having worked on at least two production use cases in this domain, you are adept at selecting models and approaches based on specific use cases and their solutions. You comprehend that model building is just a part of production AI work and are familiar with maintaining high-performance AI systems. With over 6 years of experience in building and maintaining large-scale production AI systems, including optimization and tuning for deployment at scale, you ensure reliability and efficiency. Your insatiable curiosity and enthusiasm for cutting-edge research drive you to apply innovative approaches to real-world problems. Proficiency in Python and its standard libraries, along with strong skills in monitoring and debugging production AI systems for sustained reliability and efficiency, are part of your expertise. You also excel in mentoring and guiding junior engineers, sharing your knowledge to enhance the team's skills. Your ability to engage with various stakeholders, including senior leadership and demanding industry customers, is commendable. Additionally, you have some familiarity with AI Ops and related tooling to streamline AI processes and cloud experience with AWS/GCP/Azure. Desirable skills include experience with other languages, familiarity with Docker and Kubernetes for efficient service deployment, and exposure to various platforms, frameworks, and tools in the AI and machine learning ecosystem. Furthermore, any publications and patents in the AI domain would be advantageous.,

We are looking for a highly skilled and experienced Senior Python & ML Engineer with expertise in PySpark, machine learning, and large language models (LLMs). You will play a key role in designing, developing, and implementing scalable data pipelines, machine learning models, and LLM-powered applications. In this role, you will need to have a solid understanding of Python's ecosystem, distributed computing using PySpark, and practical experience in AI optimization. Your responsibilities will include designing and maintaining robust data pipelines with PySpark, optimizing PySpark jobs for efficiency on large datasets, and ensuring data integrity throughout the pipeline. You will also be involved in developing, training, and deploying machine learning models using key ML libraries such as scikit-learn, TensorFlow, and PyTorch. Tasks will include feature engineering, model selection, hyperparameter tuning, and integrating ML models into production systems for scalability and reliability. Additionally, you will research, experiment with, and integrate state-of-the-art Large Language Models (LLMs) into applications. This will involve developing solutions that leverage LLMs for tasks like natural language understanding, text generation, summarization, and question answering. You will also fine-tune pre-trained LLMs for specific business needs and datasets, and explore techniques for prompt engineering, RAG (Retrieval Augmented Generation), and LLM evaluation. Collaboration is key in this role, as you will work closely with data scientists, engineers, and product managers to understand requirements and translate them into technical solutions. You will mentor junior team members, contribute to best practices for code quality, testing, and deployment, and stay updated on the latest advancements in Python, PySpark, ML, and LLMs. Furthermore, you will be responsible for deploying, monitoring, and maintaining models and applications in production environments using MLOps principles. Troubleshooting and resolving issues related to data pipelines, ML models, and LLM applications will also be part of your responsibilities. To be successful in this role, you should have a Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field. Strong proficiency in Python programming, PySpark, machine learning, and LLMs is essential. Experience with cloud platforms like AWS, Azure, or GCP is preferred, along with strong problem-solving, analytical, communication, and teamwork skills. Nice-to-have skills include familiarity with R and Shiny, streaming data technologies, containerization technologies, MLOps tools, graph databases, and contributions to open-source projects.,

About Us At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities, and shareholders every day. One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We're devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being. Bank of America believes both in the importance of working together and offering flexibility to our employees. We use a multi-faceted approach for flexibility, depending on the various roles in our organization. Working at Bank of America will give you a great career with opportunities to learn, grow, and make an impact, along with the power to make a difference. Join us! Global Business Services Global Business Services delivers Technology and Operations capabilities to Lines of Business and Staff Support Functions of Bank of America through a centrally managed, globally integrated delivery model and globally resilient operations. Global Business Services is recognized for flawless execution, sound risk management, operational resiliency, operational excellence, and innovation. In India, we are present in five locations and operate as BA Continuum India Private Limited (BACI), a non-banking subsidiary of Bank of America Corporation and the operating company for India operations of Global Business Services. Process Overview Document, Content & Record Services Technology (DCRS) is an enterprise-wide capability, managing documents, e-signature transactions, and the creation, storage, and fulfillment of billions of letters and statements annually. DCRS capabilities are at the forefront of the digital evolution as they drive a significant reduction in paper and manual processes. Job Description - 7+ years as Data Scientist or related roles - Deep understanding and some exposure to new Gen AI Open-source Models - At least 5 years programming experience in software development and Agile processes - At least 5 years Python (or equivalent) programming experience to work with ML/NLP models - We're looking for a Python Developer who can be responsible for designing, building, and maintaining document capture applications - The ideal candidate will have a solid background in software engineering with experience in building Machine Learning & NLP Models and good familiarity with Gen AI Models Responsibilities - Building Machine Learning & NLP Models and knowledge of new Gen AI Open-source Models Requirements - Experience in setting up supervised & unsupervised learning ML/NLP models including data cleaning, data analytics, feature creation, model selection & ensemble methods, performance metrics & visualization - Experience in ML/NLP development pipelines of large datasets, both structured & unstructured - At least 2 years" experience in designing and developing enterprise-scale ML/NLP solutions in one or more of: Named Entity Recognition, Document Classification, Document Summarization, Topic Modeling, Dialog Systems, Sentiment Analysis, OCR text processing - Knowledge and hands-on experience working with OCR products Education - Bachelors /masters degree in computer science/data science, or a related technical field - Certifications If Any: NA Experience Range - 06 Years To 12 Years Foundational Skills - Good experience as Data Scientist or related roles - Deep understanding and some exposure to new Gen AI Open-source Models - At least 5 years programming experience in software development and Agile processes - At least 5 years Python (or equivalent) programming experience to work with ML/NLP models - Experience in setting up supervised & unsupervised learning ML/NLP models including data cleaning, data analytics, feature creation, model selection & ensemble methods, performance metrics & visualization - Experience in ML/NLP development pipelines of large datasets, both structured & unstructured - At least 2 years" experience in designing and developing enterprise-scale ML/NLP solutions in one or more of: Named Entity Recognition, Document Classification, Document Summarization, Topic Modeling, Dialog Systems, Sentiment Analysis, OCR text processing - Knowledge and hands-on experience working with OCR products Desired Skills - Collaborating with a diverse set of partners and stakeholders from various Lines of Business - Highly motivated, proactive, and a self-starter; strong sense of ownership & ability to create and execute plans without daily oversight - Critical thinker: ability to analyze problems and identify issues and provide solutions - Ability to navigate the enterprise & data assets across multiple functions - Highly organized - Effectively prioritizes and balances multiple efforts in a fast-paced environment - Excellent communication and Presentation skills - Analytical abilities & great problem-solving skills Work Timings - 11:00 AM to 8:00 PM IST Job Location - Mumbai, Gurugram, GIFT, Chennai,

Job Title: Machine Learning Engineer Location: Bhubaneswar Experience: 4-8 Years Job Description: We are looking for a talented Machine Learning Engineer with 4-8 years of experience to join our team. The ideal candidate will have a strong background in designing, developing, and deploying machine learning models and algorithms to solve complex business problems. You will be responsible for analyzing large datasets, identifying patterns, and creating predictive models to drive business insights and optimization. Key Responsibilities: Develop, implement, and optimize machine learning algorithms to solve business problems. Analyze large datasets to extract valuable insights and patterns for decision-making. Collaborate with cross-functional teams to integrate machine learning solutions into business processes. Conduct model training, evaluation, and fine-tuning to improve accuracy and performance. Stay up-to-date with the latest trends and advancements in machine learning and AI. Must-Have Skills: Strong experience in machine learning frameworks and libraries (TensorFlow, Scikit-learn, Keras, etc.). Proficiency in programming languages like Python or R. Hands-on experience in data preprocessing, feature engineering, and model selection. Knowledge of algorithms for classification, regression, and clustering. Strong understanding of statistics, mathematics, and data modeling. If you are passionate about machine learning and eager to apply your skills to impactful projects, apply now to join our growing team! Job Type: Full-time Schedule: Day shift Morning shift Work Location: In person,