1435 Deep Learning Jobs - Page 18

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Job Description: Graduate degree in a quantitative field (CS, statistics, applied mathematics, machine learning, or related discipline) • Good programming skills in Python with strong working knowledge of Pythons numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, etc. • Experience with LMs (Llama (1/2/3), T5, Falcon, Langchain or framework similar like Langchain) • Candidate must be aware of entire evolution history of NLP (Traditional Language Models to Modern Large Language Models), training data creation, training set-up and finetuning • Candidate must be comfortable interpreting research papers and architecture diagrams of Language Models • Candidate must be comfortable with LORA, RAG, Instruct fine-tuning, Quantization, etc. • Predictive modelling experience in Python (Time Series/ Multivariable/ Causal) • Experience applying various machine learning techniques and understanding the key parameters that affect their performance • Experience of building systems that capture and utilize large data sets to quantify performance via metrics or KPIs • Excellent verbal and written communication • Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects. Roles & Responsibilities: • Lead a team of Data Engineers, Analysts and Data scientists to carry out following activities: • Connect with internal / external POC to understand the business requirements • Coordinate with right POC to gather all relevant data artifacts, anecdotes, and hypothesis • Create project plan and sprints for milestones / deliverables • Spin VM, create and optimize clusters for Data Science workflows • Create data pipelines to ingest data effectively • Assure the quality of data with proactive checks and resolve the gaps • Carry out EDA, Feature Engineering & Define performance metrics prior to run relevant ML/DL algorithms • Research whether similar solutions have been already developed before building ML models • Create optimized data models to query relevant data efficiently • Run relevant ML / DL algorithms for business goal seek • Optimize and validate these ML / DL models to scale • Create light applications, simulators, and scenario builders to help business consume the end outputs • Create test cases and test the codes pre-production for possible bugs and resolve these bugs proactively • Integrate and operationalize the models in client ecosystem • Document project artifacts and log failures and exceptions. • Measure, articulate impact of DS projects on business metrics and finetune the workflow based on feedbacks

Role & responsibilities AI developer with Web, Mobile, AI, Android, Flutter, PHP, REACT-NODE, python-django, ML/DL Internships are available For Junior developers, we will train you in live AI/IOT/Web/Mobile projects. Full time opportunity after Successful Internships. Additional training will be provided for freshers along with Master degree enrollments. Preferred candidate profile Fast self learner. AI with Full stack exposure to REACT,NODE,JSP, PHP-Laravel, Python-django, Android, etc . Good understanding of complex Data base and SQL with healthcare and business application exposure is required.

We are seeking a Data Scientist with 2 to 5 years of experience to join our AI/ML team. The ideal candidate will work under the guidance of a team lead to develop and implement machine learning solutions, with a focus on Natural Language Processing (NLP) and generative AI applications. Key Responsibilities: Develop and maintain NLP models and chatbot solutions under the direction of the team lead Implement machine learning algorithms and deep learning models using Python Process, clean, and validate data to ensure high-quality model inputs Create and optimize generative AI solutions for various business applications Collaborate with team members to improve existing models and develop new solutions Document technical processes and maintain codebase Participate in code reviews and team discussions Debug and troubleshoot models to improve performance Monitor model performance and implement necessary updates Prepare and briefing for client presentation Candidate Specification: Bachelor's degree in Computer Science, Data Science, or related field 2+ years of professional experience in data science or machine learning Experience with large language models and transformer architectures Familiarity with chatbot development using RASA (preferable) or other platform Knowledge of MLOps practices and tools Familiarity with cloud platforms (AWS/Azure/GCP) Knowledge on REST APIs Background in implementing production-grade ML solutions Strong proficiency in Python programming Hands-on experience with NLP libraries and frameworks (e.g., NLTK, spaCy, Transformers) Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) Knowledge of chatbot development and conversational AI Understanding of generative AI concepts and applications Familiarity with version control systems (e.g., Git) Strong analytical and problem-solving skills Technical Skills: Programming Languages:Python (required) ML/AI Frameworks: TensorFlow, PyTorch, scikit-learn NLP Tools: NLTK, spaCy,Hugging Face Transformers Version Control: Git Data Processing: Pandas, NumPy Development Tools: VS Code Soft Skills: Excellent oral and written communication skills Good at client interaction and client communication Presentation skill Good comprehension and articulator Strong team player with ability to take direction from lead Detail-oriented approach to problem-solving Ability to work in a fast-paced environment Good time management skills Eagerness to learn and adapt to new technologies Perks and Benefits: 5 days working Good work environment Great learning opportunity Work life balance

Experience: 7-12years Location and Work Mode: Pune Job Description: About this Role We are seeking a highly skilled and motivated Data Scientist to join our team. This role is ideal for individuals who are passionate about leveraging data to drive innovation and create intelligent, scalable solutions. The successful candidate will work across a variety of data science domains, including diagnostic, predictive, and prescriptive analytics, and will contribute to the development of autonomous cognitive systems. This is an exciting opportunity to be part of a forward-thinking team that values continuous learning and collaboration. Who are you A data enthusiast with a strong foundation in machine learning, deep learning, and statistical modelling. A collaborative problem-solver who thrives in cross-functional teams and is comfortable engaging with stakeholders. A continuous learner with a passion for exploring new tools, technologies, and methodologies. An effective communicator who can translate complex data insights into actionable business strategies. A self-starter with a proactive mindset and the ability to work independently in a dynamic environment. What you will do Manage and process large-scale data on both on-premise and cloud platforms (preferably AWS). Design and implement diagnostic models using decision theory and causal inference techniques (e.g., DAG, ADMG, Deterministic SME). Build and productise diagnostic systems for scalable reuse across the organisation. Develop robust predictive and prescriptive analytics models using AI techniques such as ML, DL, NLP, ES, and RL. Create intelligent systems that determine the Next Best Action based on prescriptive analytics. Drive the development of autonomous cognitive systems that proactively recommend actions with minimal human intervention. Apply advanced deep learning techniques including CNNs, RNNs, and MLPs to solve complex business problems. Utilise machine learning and deep learning libraries such as TensorFlow, PyTorch, Scikit-learn, NumPy, Pandas, Statsmodels, Theano, and XGBoost. Collaborate with stakeholders to understand business needs and deliver data-driven solutions. Present insights and findings using visualisation tools like Tableau and Power BI. What skills you need Proficiency in programming languages: Python, R, SQL Experience with frameworks: TensorFlow, Keras, Scikit-learn Strong understanding of statistical modelling: regression, classification, clustering, time series Hands-on experience with cloud platforms: AWS (preferred), Azure Familiarity with big data technologies and environments Excellent communication and stakeholder management skills Strong analytical and problem-solving abilities At least one certification in AWS is preferred What skills you will learn Advanced applications of causal inference and decision theory in real-world scenarios Building and deploying scalable AI systems in cloud environments Designing autonomous systems that integrate feedback loops for continuous learning Enhancing stakeholder engagement through data storytelling and visualisation Exposure to cutting-edge tools and frameworks in the AI and ML ecosystem

Job Title : AI/ML Engineer (with LLM, Azure, Python & PySpark expertise) Job Description : We are looking for a skilled and experienced AI/ML Engineer to join our data science and AI team. The ideal candidate will have a strong foundation in machine learning, artificial intelligence, and large language models (LLMs), along with deep proficiency in Python, PySpark, and Microsoft Azure services. You will be responsible for developing and deploying scalable AI solutions, working with big data frameworks, and leveraging cloud platforms to operationalize machine learning models. Key Responsibilities : Artificial Intelligence (AI) & Machine Learning (ML): Design, develop, and optimize machine learning and AI models to solve business problems. Perform exploratory data analysis and feature engineering for model development. Use supervised, unsupervised, and reinforcement learning techniques where appropriate. Build AI pipelines and integrate models into production systems. Large Language Models (LLM): Fine-tune and deploy LLMs (e.g., OpenAI, Hugging Face, or custom-trained models). Develop prompt engineering strategies for LLM applications. Implement RAG (Retrieval-Augmented Generation) systems or LLMOps workflows. Evaluate LLM outputs for accuracy, bias, and performance. Python Programming: Write efficient, reusable, and testable Python code for data processing, modeling, and API services. Build automation scripts for data pipelines and model training workflows. Use popular libraries such as Scikit-learn, TensorFlow, PyTorch, Pandas, and NumPy. PySpark and Big Data: Work with large datasets using PySpark for data wrangling, transformation, and feature extraction. Optimize Spark jobs for performance and scalability. Collaborate with data engineering teams to implement end-to-end data pipelines. Microsoft Azure: Deploy models and applications using Azure ML, Azure Databricks, Azure Functions, and Azure Synapse. Manage compute resources, storage, and data security on Azure. Use Azure DevOps for CI/CD of ML pipelines and automation. Cross-Functional Collaboration & Documentation: Collaborate with data engineers, product managers, and business stakeholders to align technical solutions with business needs. Maintain clear documentation of models, code, and workflows. Present technical findings and model outcomes to both technical and non-technical audiences. Required Skills & Qualifications : Bachelor's or Masters degree in Computer Science, Data Science, Engineering, or a related field. 3+ years of experience in AI/ML and data engineering roles. Proficient in Python and PySpark. Experience with cloud platforms, especially Microsoft Azure. Hands-on experience with LLMs (e.g., GPT, BERT, Claude, etc.). Familiarity with ML frameworks like Scikit-learn, TensorFlow, or PyTorch. Solid understanding of ML lifecycle, MLOps, and deployment strategies. Nice to Have : Experience with LLMOps and vector databases (e.g., FAISS, Pinecone). Knowledge of data governance and responsible AI practices. Azure certifications (e.g., Azure AI Engineer Associate, Azure Data Scientist Associate). Experience with REST APIs and containerization (Docker, Kubernetes).

Role & responsibilities: Outline the day-to-day responsibilities for this role. Preferred candidate profile: Specify required role expertise, previous job experience, or relevant certifications.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Experience: Minimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role. Proven experience in banking or financial services is highly preferred. Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark). Experience in Azure ML tools: Databricks etc. Experience with end-to-end model lifecycle management and MLOps. Minimum Qualification: Masters Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.

Job Responsibilities Craft winning proposals to grow the Data Science Practice. Develop and operationalize scalable processes to deliver on large & complex client engagements. Ensure profitable delivery and great customer experience design the end to end solution, put together the right team and deliver as per established processes. Build an A team hire the required skills sets and nurture them in a supporting environment to develop strong delivery teams for the Data Science Practice. Train and mentor staff and establish best practices and ways of working to enhance data science capabilities at Axtria. Operationalize an eco-system for continuous learning & development. Write white papers, collaborate with academia and participate in relevant forums to continuously upgrade self knowledge & establish Axtrias thought leadership in this space. Research, develop, evaluate, and optimize newly emerging algorithms and technologies for relevant use cases in pharma commercial & clinical space.EducationBachelor Equivalent - OtherPG Diploma in ManagementWork ExperienceData Scientist6-15 years of relevant experience in advanced statistical and mathematical models and predictive modeling using Python. Experience in the data science space prior relevant experience in Artificial intelligence and machine Learning algorithms for developing scalable models supervised and unsupervised techniques like NLP and deep Learning Algorithms. Ability to build scalable models using Python, R-Studio, R Shiny, PySpark, Keras, and TensorFlow. ML Ops Engineering6-15 years of experience with MLOps Frameworks like Kubeflow, MLFlow, Data Robot, Airflow, etc., experience with Docker and Kubernetes, OpenShift. Prior experience in end-to-end automated ecosystems including, but not limited to, building data pipelines, developing & deploying scalable models, orchestration, scheduling, automation, and ML operations. Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS, MS Azure, or GCP).Gen AI 6-15 years develop, test, and deploy Python based applications on Azure/AWS platforms. Must have basic knowledge on concepts of Generative AI / LLMs / GPT. Deep understanding of architecture and work experience on Web Technologies. Python, SQL hands-on experience. Expertise in any popular python web frameworks e.g. flask, Django etc. Familiarity with frontend technologies like HTML, JavaScript, REACT.IOS Developer 6+ years of experience in IOS mobile development and 5+ in React Native. Strong background working with React Native tools. Fullstack Developer 6-15 years experience to develop, test and deploy React, Javascript, Python based applications on Azure/AWS platforms. Must have experience working on frontend and backend technologies. Experience on React and Python is a must.Technical CompetenciesML Data ScienceML OpsML engineeringPharmaPythonPySparkAWS Data PipelineAWS EMRAIMLNLPBehavioural CompetenciesOwnershipTeamwork & LeadershipTalent ManagementCultural FitMotivation to Learn and GrowProject Management

Okta is seeking a highly skilled Full-Stack Engineer with deep expertise in AWS Bedrock, generative AI, and modern software development to join our fast-moving team at the intersection of developer experience, machine learning, and enterprise software. As part of the Okta Business Technology (BT) team, you will build cutting-edge tools that make AI development intuitive, collaborative, and scalable. If you're passionate about building next-generation AI applications and empowering developers through innovative platforms, this is the role for youJob Duties and Responsibilities Design and develop full-stack applications that integrate seamlessly with Amazon Bedrock AI agents. Build scalable, production-grade AI/ML solutions using AWS Bedrock and the AWS Agent Development Kit. Implement back-end services and APIs to interact with foundation models for tasks such as automated sourcing, content generation, and prompt orchestration. Create intuitive and performant front-end interfaces using Angular that connect with GenAI capabilities. Ensure seamless integration of LLMs and foundation models into the broader application architecture. Explore and rapidly prototype with the latest LLMs and GenAI tools to iterate on new capabilities and features. Build sophisticated AI workflows using knowledge bases, guardrails, and prompt chaining/flows. Deploy and maintain enterprise-ready GenAI applications at scale. Collaborate with business analysts to understand customer needs and use cases, and work with the team to design, develop POCs to test, implement & support solutions Foster strong relationships with teammates, customers, and vendors to facilitate effective communication and collaboration throughout the project lifecycle Perform in-depth analysis of requirements, ensuring compatibility and adherence to established standards and best practicesRequired Skills: 7+ years of robust experience with hands-on development & design experience 3+ years of experience in one or more of the following areasDeep Learning, LLMs, NLP, Speech, Conversational AI, AI Infrastructure, Fine-tuning, and optimizations of PyTorch models. Software development experience in languages like Python (must have) and one from the optional (Go, Rust, and C/C++). Experience with at least one LLM such as Llama, GPT, Claude, Falcon, Gemini, etc. Expertise in AWS Bedrock and the AWS Agent Development Kit is mandatory Hands-on experience with Python libraries including boto3, NumPy, Pandas, TensorFlow or PyTorch, and Hugging Face Transformers Solid understanding of the AWS ecosystem (e.g., CloudWatch, Step Functions, Kinesis, Lambda) Familiarity with full software development lifecycle, including version control, CI/CD, code reviews, automated testing, and production monitoring Knowledge about the ERP, HR technology and Legal business processes is an advantageEducation and Certifications Bachelors degree in Computer Science or a related field, or equivalent practical experience AWS certifications (e.g., AWS Certified Solutions Architect, Machine Learning Specialty) are a plus Experience working with large-scale generative AI or LLM-based applications Knowledge of secure application development and data privacy practices in AI/ML workloads"This role requires in-person onboarding and travel to our Bengaluru, IN office during the first week of employment."

We, at the LVPEI Center for Innovation, have developed a variety of screening and diagnostic devices Precision imaging systems are crucial components of these devices and the visual information captured here helps the clinician / examiner to decide the status of the eye health To auto-detect and quantify various pathologies of eye we adopt Computer Vision and Machine Learning techniques These developments will help the innovation center to build automated disease detection systems and there by enhance quality of eye care This role gives the candidate an opportunity to work on unique data sets and explore various image processing algorithms and deep learning (algorithms & frameworks) This role majorly involves in organizing data for further analysis, making the models scalable and light-weight to implement them offline on mobile phone platforms Responsibilities Work on translating the computer vision research to its applications in screening and diagnosing eye pathologies. Create novel methods to annotate and organize the patient data for further analysis. Keep UpToDate with the rapid developments in Computer vision and deep learning Incorporate improvements to the model / algorithms design and architecture, leading to increased accuracy in pathology identification. Collaborate with interns at the center to Fastrack the development process. Conceptualize a development task, its dependencies and map out work flows for an assigned project Best practices of software documentation and maintian development logs. Required Skills First-hand experience in working with open source neural networks like ResNet /MobileNet /Inception. Experience of working with at least one among PyTorch / TensorFlow / Keras / MXNet / Theano Strong background in Data Science, data structures, statistics, algorithms like Regression, Classification Sound understanding in the areas of Computer Vision / Pattern Recognition / Image Processing. Online certifications will be an added advantage.

- Data Scientist -6+ years of experience in data science, with at least 2 years focused on LLMs or Generative AI. -Proven implementation experience in Data Science, Machine Learning, Deep Learning, and NLP for multiple domains. -Strong programming skills in Python, with experience in libraries such as Transformers (Hugging Face), PyTorch, or TensorFlow. -Hands-on experience with fine-tuning, prompt engineering, RAG (Retrieval-Augmented Generation), and LLM evaluation. -Familiarity with vector databases and embedding techniques. -Experience deploying models using APIs, Docker, and cloud platforms -Strong analytical, problem-solving, and communication skills. -Experience in ML Ops, Model deployment, Model lifecycle and management

Dear Candidate, We have an urgent opening with one of Multinational Company for Below Locations. Interested candidate can share the resume on Deepaksharma@thehrsolutions.in OR WhatsApp on 8882505093 Experience : 9+ Years Profile : ML Engineer (Advanced AI/ML + Python) Locations : Hyderabad, Bangalore, Mumbai, Kolkata Notice period : Only immediate joiners OR Already serving. Job Description - ML Engineer (Advanced AI/ML + Python) This role leverages machine learning & advanced AI services to generate business insights 8+ Years of relevant experience in Machine learning & Deep learning (GenAI-optional) experience Experience in deploying NLP, CV & Deep learning algorithms Experience in leading teams and managing the end-to-end deliverables. Exposure to MLOps implementations Leadership abilities to guide and mentor junior team members. Design and implement scalable and reliable ML pipelines for model training, evaluation and deployment Advanced degree in Data Science, Statistics, Computer Science, or a related field. Proficiency in Python, Git, Github,Pyspark, Pytorch, , SQL and strong expertise of AI/ML algorithms is essential with knowledge of AWS cloud ML services. Strong analytical skills & communication skills. Ability to interpret complex data sets. Responsibilities- Lead the development and implementation of predictive models and machine learning algorithms. Design and implement scalable and reliable ML pipelines for model training, evaluation and deployment Collaborate with CMA CGM cross-functional teams to understand business needs and devise possible solutions. Present and visualize data insights to stakeholders in a comprehensible manner.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

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

An AI Data Scientist at IBM is not just a job title - it’s a mindset. You’ll leverage the watsonx,AWS Sagemaker,Azure Open AI platform to co-create AI value with clients, focusing on technology patterns to enhance repeatability and delight clients. We are seeking an experienced and innovative AI Data Scientist to be specialized in foundation models and large language models. In this role, you will be responsible for architecting and delivering AI solutions using cutting-edge technologies, with a strong focus on foundation models and large language models. You will work closely with customers, product managers, and development teams to understand business requirements and design custom AI solutions that address complex challenges. Experience with tools like Github Copilot, Amazon Code Whisperer etc. is desirable. Success is our passion, and your accomplishments will reflect this, driving your career forward, propelling your team to success, and helping our clients to thrive. Day-to-Day Duties: Proof of Concept (POC) DevelopmentDevelop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another, particularly COBOL to JAVA through rapid prototypes/ PoC Documentation and Knowledge SharingDocument solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides. Contribute to internal knowledge sharing initiatives and mentor new team members. Industry Trends and InnovationStay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g. Kubernetes, AWS, Azure, GCP) and related services is a plus. Experience and working knowledge in COBOL & JAVA would be preferred Having experience in Code generation, code matching & code translation leveraging LLM capabilities would be a Big plus (e.g. Amazon Code Whisperer, Github Copilot etc.) * Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI. Growth mindsetDemonstrate a growth mindset to understand clients' business processes and challenges. Experience in python and pyspark will be added advantage Preferred technical and professional experience ExperienceProven experience in designing and delivering AI solutions, with a focus on foundation models, large language models, exposure to open source, or similar technologies. Experience in natural language processing (NLP) and text analytics is highly desirable. Understanding of machine learning and deep learning algorithms. Strong track record in scientific publications or open-source communities Experience in full AI project lifecycle, from research and prototyping to deployment in production environments

Work with broader team to build, analyze and improve the AI solutions. You will also work with our software developers in consuming different enterprise applications Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Resource should have 5-7 years of experience. Sound knowledge of Python and should know how to use the ML related services. Proficient in Python with focus on Data Analytics Packages. Strategy Analyse large, complex data sets and provide actionable insights to inform business decisions. Strategy Design and implementing data models that help in identifying patterns and trends. Collaboration Work with data engineers to optimize and maintain data pipelines. Perform quantitative analyses that translate data into actionable insights and provide analytical, data-driven decision-making. Identify and recommend process improvements to enhance the efficiency of the data platform. Develop and maintain data models, algorithms, and statistical models Preferred technical and professional experience Experience with conversation analytics. Experience with cloud technologies Experience with data exploration tools such as Tableu

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Large Language Models Good to have skills : NAMinimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI/ML Engineer, you will develop applications and systems utilizing AI tools, Cloud AI services, and GenAI models. Your role involves creating cloud or on-prem application pipelines with production-ready quality, incorporating deep learning, neural networks, chatbots, and image processing. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Expected to provide solutions to problems that apply across multiple teams.- Lead the implementation of large language models in AI applications.- Research and apply cutting-edge AI techniques to enhance system performance.- Contribute to the development and deployment of AI solutions across various domains. Professional & Technical Skills: - Must To Have Skills: Proficiency in Large Language Models.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 12 years of experience in Large Language Models.- This position is based at our Hyderabad office.- A 15 years full-time education is required. Qualification 15 years full time education

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Good to have skills : NAMinimum 15 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI / ML Engineer, you will engage in the development of applications and systems that leverage artificial intelligence tools and cloud AI services. Your typical day will involve designing and implementing production-ready solutions, ensuring that they meet quality standards. You will work with various AI models, including generative AI, deep learning, and neural networks, while also exploring innovative applications such as chatbots and image processing. Collaboration with cross-functional teams will be essential as you contribute to the overall success of projects and drive advancements in AI technology. Roles & Responsibilities:- Expected to be a Subject Matter Expert with deep knowledge and experience.- Should have influencing and advisory skills.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Expected to provide solutions to problems that apply across multiple teams.- Facilitate knowledge sharing sessions to enhance team capabilities and understanding of AI technologies.- Mentor junior professionals to foster their growth and development in AI and machine learning. Professional & Technical Skills: - Must To Have Skills: Proficiency in Machine Learning.- Experience with cloud-based AI services and deployment strategies.- Strong understanding of deep learning frameworks such as TensorFlow or PyTorch.- Familiarity with data preprocessing and feature engineering techniques.- Ability to design and implement neural networks for various applications. Additional Information:- The candidate should have minimum 15 years of experience in Machine Learning.- This position is based at our Bengaluru office.- A 15 years full time education is required. Qualification 15 years full time education