1384 Deep Learning Jobs - Page 46

Job Overview: We are seeking a talented and driven Machine Learning Engineer to design and optimize machine learning models that will enhance a variety of credit and operational processes. This role will involve building cutting-edge solutions in areas like underwriting, loan processing, fraud detection, and risk mitigation, while continuously driving improvements through innovation and advanced techniques. Key Responsibilities: - Model Development & OptimizationDesign, deploy, and refine machine learning models to support key functions such as underwriting, account management, fraud detection, and loss prevention. - Advanced Techniques ImplementationIdentify opportunities to implement advanced machine learning approaches-such as Natural Language Processing (NLP), Image Recognition, and Graph Mining-to address complex business challenges. - Collaboration & Knowledge SharingWork with internal and external resources, as well as open-source algorithms, to find the best solutions and improve model performance. - Risk Management CompliancePartner with the Model Risk Management team to ensure models are developed with appropriate rigor and align with risk management and governance standards. - Cross-Functional CollaborationCollaborate closely with Product and Engineering teams to ensure seamless model deployment and integration. - Performance MonitoringTrack the effectiveness of models through dashboards and key performance indicators (KPIs), ensuring continuous improvement. - Stakeholder CommunicationPresent model insights and performance reports to key stakeholders in Credit, Risk, and Business Units, making complex findings accessible and actionable. Qualifications: - Educational BackgroundBachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. A Master's degree is highly preferred. - Experience6-12 years of hands-on experience developing and implementing machine learning models in a professional environment. - Technical ProficiencyStrong expertise in SQL and Python, with the ability to write efficient code for working with large datasets and creating advanced features. - Analytical ThinkingExceptional attention to detail and an ability to uncover hidden data patterns through thorough investigation. - Machine Learning ExpertiseSolid foundation in machine learning and statistical modeling, including supervised and unsupervised learning techniques like regression, decision trees, support vector machines, boosting, deep learning, and more. Must stay current with industry advancements to apply the best techniques. - Database KnowledgeProficient in working with SQL, NoSQL, Hive, and other relevant database technologies. - Effective CommunicationStrong ability to translate complex technical concepts into clear, understandable terms for non-technical stakeholders. Apply Save Save Pro Insights

About The Role : As a Banking Data Analyst, you will play a critical role in our clients' data-driven decision-making processes. You will work closely with marketing teams, product managers, and other stakeholders to understand their data needs and provide relevant analyses. Your expertise in SQL, marketing analytics, and banking domain knowledge will be essential to your success. Responsibilities : - Perform in-depth data analysis using SQL to extract and analyze banking data. - Develop and maintain reports and dashboards to track key performance indicators (KPIs). - Identify trends and patterns in banking data to provide actionable insights. - Analyze marketing campaign performance and provide recommendations for optimization. - Segment customer data to identify target audiences for marketing initiatives. - Develop and implement customer lifetime value (CLTV) models. - Apply knowledge of banking products and services to analyze data and provide relevant insights. - Focus on data related to deposits and home lending (good to have). - Visualize data using tools like Jupyter Notebook to communicate insights effectively. - Present findings to stakeholders in a clear and concise manner. - Ensure data accuracy and integrity. - Identify and resolve data quality issues. - Utilize Python for data analysis and automation tasks (good to have). Required Skills : - Very strong SQL skills for data extraction and analysis. - Proven experience in marketing analytics, including campaign analysis and customer segmentation. - Experience in the banking industry, with a focus on deposits and home lending (good to have). - Experience with Jupyter Notebook for data visualization and reporting. Good to Have Skills : Python Programming : - Experience with Python for data analysis and automation. Apply Insights Follow-up Save this job for future reference Did you find something suspiciousReport Here! Hide This Job Click here to hide this job for you. You can also choose to hide all the jobs from the recruiter.

Position Title: Pro Vice-Chancellor Computer Engineering Background Location: Bengaluru North, Karnataka, India Role Overview: The Pro Vice-Chancellor (PVC) will play a pivotal role in shaping and leading the academic and research vision of technology and engineering schools with a core emphasis on Computer Science and allied disciplines. The position requires an accomplished academician with strong subject knowledge, technological foresight, and the ability to lead cutting-edge research, foster innovation, and build robust academia-industry linkages. Key Responsibilities: Academic and Technical Leadership: Research and Innovation Leadership: Technology Incubation and Start-Up Ecosystem: Academic-Industry Collaboration: Digital Transformation and Smart Campus Initiatives: Internationalization: Faculty and Talent Development: Strategic Planning and Policy Implementation: Eligibility Criteria: Mandatory Qualifications: Engineering Graduation (B.E. / B.Tech), Post-Graduation (M.E. / M.Tech), and Doctorate (Ph.D.) in any one of the following disciplines only: Computer Science Information Science Information Technology Data Science Artificial Intelligence & Machine Learning Note: Candidates with engineering graduation in any other specialization will not be considered. Candidates with qualifications such as B.Sc., BCA, MCA, or other non-engineering degrees will also not be eligible. Experience Requirements: Minimum 15 years of academic experience, including teaching, research, and academic administration. Demonstrated leadership in funded research projects, Ph.D. guidance, patents, and high-impact publications. Experience in establishing or leading research labs, innovation centers, or CoEs. Preferred Attributes: Academic qualifications from premier national/international institutions (e.g., IITs, NITs, IIITs, global universities). Strong industry interface with a track record in consulting, technology advisory, or product development. Global exposure through research collaborations, academic visits, or international program management.

Role Summary: The Technical Lead/Manager will be responsible for leading the AI CoE team, driving the implementation of AI-powered solutions for the organization. They will coordinate across multiple teams, work closely with stakeholders, and oversee the technical aspects of AI/ML projects, ensuring the effective application of generative AI technologies to the product suite. Key Responsibilities: Lead the AI CoE team, ensuring alignment with business objectives. Oversee the design, development, and deployment of AI/ML models for financial use cases. Work closely with product managers and business stakeholders to understand requirements and deliver actionable AI solutions. Provide guidance and mentorship to junior team members. Manage project timelines, resources, and risk assessments. Collaborate with Data Engineers, AI/ML Engineers, Full Stack Engineers, and QA Engineers to ensure smooth integration of AI solutions. Stay updated with advancements in AI/ML technologies and best practices. Required Experience: 8-12 years of experience in AI/ML technologies, with at least 3 years in a leadership role. Strong background in AI/ML model development and deployment, particularly in the financial services sector. Proficient in Python, R, and other AI-related programming languages. Experience managing cross-functional teams in an Agile environment. Strong understanding of data science, cloud computing, and AI/ML frameworks (e.g., TensorFlow, PyTorch, etc.). Tech Specifics: Programming Languages: Expert-level proficiency in Python (e.g., NumPy, Pandas) and R for AI/ML development; familiarity with Scala is a plus. AI/ML Frameworks: Hands-on experience with TensorFlow, PyTorch, and Scikit-learn for building and optimizing models; exposure to Hugging Face for NLP/Generative AI tasks. MLOps Tools: Strong command of Docker and Kubernetes for containerization, and Jenkins or GitHub Actions for CI/CD pipelines. Cloud Platforms: Deep expertise in AWS (e.g., SageMaker, Lambda), Azure (e.g., Machine Learning Studio), or GCP (e.g., AI Platform, BigQuery) for scalable model deployment. Big Data Technologies: Working knowledge of Apache Spark or Hadoop for processing large financial datasets. Database Skills: Proficiency in SQL and experience with NoSQL databases like MongoDB or Cassandra for data integration. Generative AI: Practical experience with models like GPT, LLaMA, or BERT for applications such as automated reporting or customer chatbots.

ob Description Role: AI Developer Agentic AI Exp: 2-3 Years Work Mode: 1210 pm, Onsite( Mohali, Punjab) Job Role & Responsibilities Design, develop, and deploy Agentic AI systems capable of autonomous task execution by integrating reasoning, memory, and tool use to enable intelligent behavior across complex, multi-step workflows, Architect intelligent agents that can dynamically interact with APIs, data sources, and third-party tools to accomplish diverse objectives with minimal human intervention, Optimize performance of agentic frameworks by enhancing model accuracy, minimizing response latency, and ensuring scalability and reliability in real-world applications, Develop reusable, testable, and production-grade code, adhering to best practices in software engineering and modern AI development workflows, Collaborate with cross-functional teams, including product managers, designers, and backend engineers, to convert business requirements into modular agent behaviors, Integrate Retrieval-Augmented Generation (RAG), advanced NLP techniques, and knowledge graph structures to improve decision-making and contextual awareness of agents, Conduct rigorous profiling, debugging, and performance testing of agent workflows to identify bottlenecks and improve runtime efficiency, Write and maintain comprehensive unit, integration, and regression tests to validate agent functionality and ensure robust system performance, Continuously enhance codebases, refactor existing modules, and adopt new design patterns to accommodate evolving agentic capabilities and improve maintainability, Implement secure, fault-tolerant, and privacy-compliant designs to ensure that deployed agentic systems meet enterprise-grade reliability and data protection standards, Qualification Required Bachelors degree in computer science, or related field, Specialization or Certification in AI or ML is a plus, Technical Expertise 2+ years of hands-on experience in AI/ML/DL projects, with a strong emphasis on Natural Language Processing (NLP), Named Entity Recognition (NER), and Text Analytics, Proven ability to design and deploy Agentic AI systems?autonomous, goal-oriented agents that exhibit reasoning, memory retention, tool use, and execution of multi-step tasks, Practical expertise in agent architecture, task decomposition, and seamless integration with external APIs, databases, and tools to enhance agent capabilities, Skilled in agent prompting strategies, including dynamic prompt chaining and context management, to guide language models through intelligent decision-making workflows, Experience with Retrieval-Augmented Generation (RAG) pipelines and generative AI, with a strong focus on optimizing NLP models for low-latency, high-accuracy production use, Solid foundation in deep learning methods, recommendation engines, and AI applications within HR or similar domains, Exposure to Reinforcement Learning (RL) frameworks and holds relevant certifications or specializations in Artificial Intelligence, showcasing continuous learning and depth in the field, Minimum Skills We Look For Skills & Expertise (with Agentic AI focus) Proven experience in building Agentic AI systems, including autonomous agents capable of multi-step reasoning, memory management, and tool use, Expertise in agent design patterns, task decomposition, dynamic planning, and decision-making logic using LLMs, Skilled in integrating multi-agent coordination, goal-setting, and feedback loops to create adaptive, evolving agent behavior, Strong command over prompt engineering, contextual memory structuring, and tool calling mechanisms within LLM-powered agent workflows, Proficiency in managing agent memory (short-term, long-term, episodic) using vector databases and custom memory stores, Ability to build autonomous task execution pipelines with minimal human input, combining language models, APIs, and third-party tools, Experience with frameworks and orchestration for agent behavior tracing, logging, and failure recovery, Tools & Technologies Agentic AI Agentic Frameworks: LangChain, CrewAI, AutoGen, AutoGPT, BabyAGI for building, managing, and orchestrating intelligent agents, LLM APIs: OpenAI (GPT-4/3 5), Anthropic (Claude), Cohere, Hugging Face Transformers, Memory & Vector Databases: FAISS, Weaviate, Pinecone, Chroma for embedding-based agent memory and contextual retrieval, Prompt Management Tools: PromptLayer, LangSmith for testing, evaluating, and refining agent prompts and traces, RAG & Context Enrichment: LangChain RAG pipelines, Haystack, Milvus, Autonomy Infrastructure: Docker, FastAPI, Redis, Celery for building scalable agent runtimes, Observability: OpenTelemetry, Langfuse (or similar) for tracing agent decisions, failures, and success metrics, Testing Agentic Behavior: Integration with PyTest + mock APIs/tools to validate autonomous decision logic and fallback strategies,

Join our Team Ericssons R&D Data team is seeking a highly motivated and self-driven Machine Learning Engineer with experience in designing, developing and deploying machine learning models Qualified candidates at the intersection of data science and software engineering, ensuring that AI models are efficient, scalable, and integrated into our production systems You will work with a group of extremely high-performing engineers who design, implement, and support end-to-end SaaS solutions You are adaptable and a flexible problem-solver with an algorithmic approach, technical expertise, engineering & analytics skills, and product sense to successfully pivot/context-switch amongst many projects with a variety of scale and complexity, Responsibilities: Design, develop, and optimize machine learning models for large-scale applications, Lead the end-to-end ML model lifecycle, including data preprocessing, feature engineering, training, tuning, and deployment, Architect, train, and deploy ML and deep learning models using AWS SageMaker and other cloud-based ML services, Guide and mentor junior ML engineers, establishing best practices for model development and productionization, Collaborate cross-functionally with data scientists, software engineers, and business stakeholders to align ML solutions with business objectives, Optimize model training and inference for performance, scalability, and cost efficiency, Stay up to date with the latest ML research and integrate cutting-edge techniques into production systems, Automate model retraining, monitoring, and deployment using MLOps and CI/CD pipelines, Work with distributed computing frameworks (e-g , Spark) for large-scale data processing and training, Requirements: 5+ years of experience in machine learning, deep learning, or AI-related fields, Bachelor's, Master's, or PhD in Computer Science, AI, Data Science, or a related field, Strong programming skills in Python, Java, or C++ and expertise in ML frameworks like TensorFlow, PyTorch, or JAX, Extensive hands-on experience with AWS, including SageMaker, S3, Lambda, Step Functions, and other AI/ML services, Deep expertise in deep learning architectures (CNNs, RNNs, Transformers) and model training techniques, Strong knowledge of hyperparameter tuning, distributed training, and model optimization, Experience deploying and maintaining ML models in production environments at scale, Proficiency in MLOps best practices, including CI/CD pipelines, monitoring, and logging for ML models, Experience with big data processing frameworks like Spark is a plus, Strong problem-solving and leadership skills, with the ability to drive ML initiatives and mentor team members,

We are looking for a skilled and passionate AI/ML Engineer to join our team and help us build intelligent systems that leverage machine learning and artificial intelligence. You will design, develop, and deploy machine learning models, work closely with cross-functional teams, and contribute to cutting-edge solutions that solve real-world problems. Key Responsibilities: Design and implement machine learning models and algorithms for various use cases (e.g., prediction, classification, NLP, computer vision). Analyze and preprocess large datasets to build robust training pipelines. Conduct research to stay up to date with the latest AI/ML advancements and integrate relevant techniques into projects. Train, fine-tune, and optimize models for performance and scalability. Deploy models to production using tools such as Docker, Kubernetes, or cloud services (AWS, GCP, Azure). Collaborate with software engineers, data scientists, and product teams to integrate AI/ML solutions into applications. Monitor model performance in production and continuously iterate for improvements. Document design choices, code, and models for transparency and reproducibility. Preferred Qualifications: Knowledge in NLP, LLM and GenAI. Knowledge in deep learning architectures such as CNNs, RNNs, transformer models. Experience with NLP libraries (e.g., Hugging Face Transformers, spaCy) or computer vision tools (e.g., OpenCV). Background in deep learning architectures such as CNNs, RNNs, GANs, or transformer models. Knowledge of MLOps practices and tools (e.g., MLflow, Kubeflow, SageMaker). Contributions to open-source AI/ML projects or publications in relevant conferences/journals.

Role & responsibilities Deliver lectures, tutorials, and lab sessions as per the curriculum. Design course materials, assessments, and learning outcomes. Guide student projects, internships, and research work. Participate in curriculum development and academic planning. Engage in scholarly research and publish in peer-reviewed journals. Attend departmental meetings and contribute to administrative responsibilities. Support institute-level activities including student development, events, and outreach. Maintain a professional, inclusive, and student-centered teaching environment. Preferred candidate profile ME/M.Tech/PhD

Visionify.ai is looking for Computer Vision / AI Engineer (Intern) to join our dynamic team and embark on a rewarding career journey Designing and developing AI algorithms and models to solve specific business problems Creating and maintaining databases for storing and processing large amounts of data Developing and deploying machine learning and deep learning models Implementing and integrating AI solutions with existing systems and software Analyzing and interpreting complex data sets to extract insights and drive decision-making Collaborating with cross-functional teams to develop and deploy AI applications Ensuring the security and privacy of data used in AI applications Communicating and presenting technical information to non-technical stakeholders Excellent communication skills & attention to detail Join our team to help develop and implement computer vision and AI algorithms for safety applications in industrial environments. Requirements: BS/MS in Computer Science, AI, or related field

Conduct cutting-edge research and develop advanced NLP algorithms and models. Build and fine-tune deep learning and machine learning models, with a focus on large language models. Work closely with internal stakeholders to define model requirements and ensure alignment with business objectives. Develop AI predictive models and perform data and model accuracy analyses. Produce and present findings, technical concepts, and model recommendations to both technical and non-technical stakeholders. Develop and maintain scripts/tools to automate both new model production and updates to existing model packages. Stay abreast of the latest advancements in data science research and contribute to the development of our knowledge base. Collaborate with developers to design automation and tool improvements for model building. Maintain documentation of processes and projects across all supported languages and environments. Have you got what it takes? Masters degree in the field of Computer Science, Technology, Engineering, Math, or equivalent practical experience Minimum of 4-7 years of data science work experience, including implementing machine learning and NLP models using real-life data. Strong research skills, with a proven track record of developing and implementing advanced machine learning algorithms. Advanced knowledge of supervised and unsupervised machine learning algorithms. Excellent proficiency in Python programming. Experience with deep learning models and libraries such as PyTorch, TensorFlow, Hands-on experience with transformer models and Gen AI frameworks (HuggingFace, AWS Bedrock, Azure Foundry ). Strong verbal and written communication skills, including effective presentation abilities. Ability to work independently and as part of a team, demonstrating analytical thinking and problem-solving skills. You will have an advantage if you also have: Experience deploying models in production environments, ensuring scalability and performance using AWS/GCP/Azure Familiarity with relational databases and query languages (eg, MSSQL) and basic SQL knowledge. Experience with Retrieval-Augmented Generation (RAG) pipelines Understanding of multimodal models (text, audio, vision). Experience in Customer Experience domains. Experience working on international, globe-spanning teams. Past participation in a formal research setting. Experience as part of a software organization

You will push the boundaries of the state-of-the-art in audio and media technologies. The ideal candidate would have a strong background in deep learning, both in terms of conceptual understanding, as well as practical experience. A core aspect of this role involves being able to keep up to date with the literature, implement, and innovate with the bleeding edge in generative models, self-supervised learning, and multi-modal learning. With the explosion of large language models and natural language processing, you will partner closely with Dolby s worldwide AI research staff, which actively pursues the integration of such models into audio and media experiences. You will be able to hit the ground running, innovate, and contribute to such projects. Consequently, experience with language models, question answering, vision-language models, captioning, etc. would be highly beneficial. Consequently, knowledge or experience in any/all of the following are helpful: Diffusion, autoregressive, or other generative models. Self-supervised, contrastive learning, auto-encoders. Audio, image, or text applications Source separation, text-to-speech, music synthesis, image segmentation, image captioning, question answering, language models, etc. Main responsibilities Partner closely with other domain experts to refine and execute Dolby s technical strategy in artificial intelligence and machine learning. Use deep learning to create new solutions (including foundation models) and enhance existing applications. Push the state-of-the-art and develop intellectual property. Transfer technology to product groups and draft patent applications. Advise internal leaders on recent deep learning advancements in the industry and academia to further influence research direction and business decisions. Requirements Ph.D. in Computer Science or similar field. A strong background in deep learning, both in terms of conceptual understanding, as well as practical experience. Strong knowledge and interest in audio processing Knowledge in video, or text processing is desirable. Strong publication record, with publications in major machine learning conferences (e.g. NeurIPS, ICLR, ICML). Publications in top domain-specific conferences is desirable (e.g., ACL, CVPR, ICASSP). Good knowledge about current machine learning literature. Highly skilled in Python and one or more popular deep learning frameworks (TensorFlow or PyTorch). Ability to envision new technologies and turn them into innovative products. Good communication and collaboration skills.

Dolby s research division is currently looking for a talented, self-motivated AI researcher to push the boundaries of the state-of-the-art in media technologies. An ideal candidate would have a strong background in deep learning, both in terms of conceptual understanding, as well as practical experience. A core aspect of this role involves staying up to date with the latest literature and driving innovation by implementing cutting-edge techniques in generative models, self-supervised learning, and multi-modal learning.. Consequently, knowledge or experience in any/all the following are helpful: Generative modeling for audio and video applications (diffusion models, autoregressive models, masked generative transformers, etc.). Multimodal semantic understanding and multimodal reasoning. Multimodal representations (that include audio and/or video). Multimodal AI architectures, with a focus on generating audio and/or video (text-to-audio, text-to-video, image-to-audio, etc.). AI-driven enhancement, processing, and generation (for audio and/or video applications). Exposure to audio and video applications (source separation, text-to-speech, music generation, image generation, image captioning, question answering, etc.) With the explosion of large language models and natural language processing, the candidate will work closely with Dolby s Machine Perception and Reasoning team to join a team of top-tier researchers working on challenging problems in multimodal AI for entertainment applications. You will focus on the creation and implementation of multimodal AI technologies from the underlying theoretical concepts to the development of prototypes and demonstrations, with the goal to create new experiences. The role will involve prototyping inspiring experiences that explore a complement of modalities. These technologies will be used to extend immersion and interaction, so the candidate should be willing to explore empirical refinement of the user experience. Main responsibilities: Work closely with other domain experts to refine and execute Dolby s technical strategy in artificial intelligence and machine learning. Use deep learning to create new solutions and enhance existing applications. Push the state-of-the-art and develop intellectual property. Mentor interns on novel research problems. Publish papers in top-tier conferences and journals. Transfer technology to product groups and draft patent applications. Advise internal leaders on recent deep learning advancements in the industry and academia to further influence research direction and business decisions. Requirements : Ph.D. in computer science or similar, with a focus on deep learning. Experience in AI applied to audio and/or video is a requirement. Technical knowledge and experience in generative modeling for audio (music, speech, sfx) or video. Strong publication record, with publications in top-tier domain specific conferences (CVPR, ICCV, ECCV, ICASSP, ISMIR), and/or machine learning conferences (e.g., NeurIPS, ICLR, ICML). Deep knowledge about current machine learning literature. Highly skilled in Python and one or more popular deep learning frameworks (TensorFlow or PyTorch) Ability to envision new technologies and turn them into innovative products. Creativity

AI Engineer - Mid Level Job Category - IT Job Type - Full Time No of openings: 01 Experience - 4 to 6 Years Job Location - Hyderabad Preferred Candidate Location - Telangana, Andhra Pradesh Apply Job Overview As an AI Engineer, you will be at the forefront of developing intelligent systems with a specialization in natural language processing (NLP). Your role involves designing, implementing, and optimizing AI models to process and Data. As an AI Engineer specializing in NLP, your work will contribute to the development of advanced applications, including conversational AI, chatbots, Task Automation and language understanding systems. This role requires a blend of technical skills, creativity, and a commitment to staying abreast of the latest advancements in AI and NLP. Roles & Responsibilities Model Development: Design and implement state-of-the-art AI models, particularly focusing on NLP tasks, using frameworks such as PyTorch, Tensorflow, Scikit-Learn. Fine-tune and adapt pre-trained models to specific applications and domains. At least 1 Year of Experience in working with Gen AI, LLM s, Prompt Engineering, Fine tuning LLM s. Must have experience and contribution in developing custom models, Large language models, fine tuning LLM s and must have open source contributions. Data Processing and Analysis: Preprocess and analyze large datasets to ensure high-quality input for training AI models. Collaborate with data engineers to build efficient pipelines for handling linguistic data. Algorithmic Development: Develop algorithms for various NLP tasks, including text classification, sentiment analysis, named entity recognition, and language generation. Experiment with different machine learning techniques to enhance model performance. Evaluation and Optimization: Implement robust evaluation metrics to assess the effectiveness of AI models. Optimize models for speed, memory usage, and scalability, ensuring efficient deployment in real-world applications. Collaboration: Collaborate with cross-functional teams, including software engineers, data scientists, and domain experts. Work closely with researchers to integrate cutting-edge AI advancements into practical solutions. Documentation and Communication: Maintain clear documentation for code, models, and processes. Communicate findings and updates to both technical and non-technical stakeholders. Qualifications Bachelors in Computer Science, Artificial Intelligence, or a related field. Proficient programming skills in languages like Python Strong expertise in deep learning frameworks WatsonX Experience is a plus Solid understanding of machine learning principles, especially in the context of language models. Experience with large-scale data processing and distributed computing. Excellent problem-solving skills and the ability to work collaboratively in a team environment. Model Development: Design and implement state-of-the-art AI models, particularly focusing on NLP tasks, using frameworks such as PyTorch, Tensorflow, Scikit-Learn. Fine-tune and adapt pre-trained models to specific applications and domains. At least 1 Year of Experience in working with Gen AI, LLM s, Prompt Engineering, Fine tuning LLM s. Must have experience and contribution in developing custom models, Large language models, fine tuning LLM s and must have open source contributions. Data Processing and Analysis: Preprocess and analyze large datasets to ensure high-quality input for training AI models. Collaborate with data engineers to build efficient pipelines for handling linguistic data. Algorithmic Development: Develop algorithms for various NLP tasks, including text classification, sentiment analysis, named entity recognition, and language generation. Experiment with different machine learning techniques to enhance model performance. Evaluation and Optimization: Implement robust evaluation metrics to assess the effectiveness of AI models. Optimize models for speed, memory usage, and scalability, ensuring efficient deployment in real-world applications. Collaboration: Collaborate with cross-functional teams, including software engineers, data scientists, and domain experts. Work closely with researchers to integrate cutting-edge AI advancements into practical solutions. Documentation and Communication: Maintain clear documentation for code, models, and processes. Communicate findings and updates to both technical and non-technical stakeholders. Qualifications Bachelors in Computer Science, Artificial Intelligence, or a related field. Proficient programming skills in languages like Python Strong expertise in deep learning frameworks WatsonX Experience is a plus Solid understanding of machine learning principles, especially in the context of language models. Experience with large-scale data processing and distributed computing. Excellent problem-solving skills and the ability to work collaboratively in a team environment.

We are seeking a talented Data Scientist II to join our team. The ideal candidate will have 2-5 years of experience in data science and possess expertise in machine learning, deep learning, Python programming, SQL, Amazon Redshift, NLP, and AWS Cloud. ** Duties and Responsibilities: Develop and implement machine learning models to extract insights from large datasets. Utilize deep learning techniques to enhance data analysis and predictive modeling. Write efficient Python code to manipulate and analyze data. - Work with SQL databases to extract and transform data for analysis. Utilize Amazon Redshift for data warehousing and analytics. Apply NLP techniques to extract valuable information from unstructured data. - Utilize AWS Cloud services for data storage, processing, and analysis. Qualifications and Requirements: Bachelors degree in Computer Science, Statistics, Mathematics, or related field. - 2-5 years of experience in data science or related field. Proficiency in machine learning, deep learning, Python programming, SQL, Amazon Redshift, NLP, and AWS Cloud. Strong analytical and problem-solving skills. - Excellent communication and teamwork abilities. * *Key Competencies - Strong analytical skills. - Problem-solving abilities. - Proficiency in machine learning and deep learning techniques. Excellent programming skills in Python. - Knowledge of SQL and database management. - Familiarity with Amazon Redshift, NLP, and AWS Cloud services. ** Performance Expectations: Develop and deploy advanced machine learning models. Extract valuable insights from complex datasets. Collaborate with cross-functional teams to drive data-driven decision-making. Stay updated on the latest trends and technologies in data science. We are looking for a motivated and skilled Data Scientist I to join our team and contribute to our data-driven initiatives. If you meet the qualifications and are passionate about data science, we encourage you to apply.

The Principal Consultant plays a vital role in providing best in class technical expertise for marketing measurement solutions. The individual will work as a Subject Matter Expert on Marketing measurement programs with a clear responsibility of bringing technical expertise in AI and engineering in the solution areas. S/he will work with data scientists and engineers to build solution prototypes, collaborate with client teams to brainstorm new AI lead solutions in measurement, become trusted advisors for key clients by bringing thought leadership and groom a set of exceptional consultants to deliver with excellence. S/he should have a client service orientation with the ability to influence the clients decision-making process, improving the overall client engagement. (Roles and Responsibilities) As a capability lead, generate client value by developing innovative solutions that solve client problems efficiently and effectively Identify opportunities to scale existing projects by bringing tools and best practices for expansion of current scope and drive productivity improvements and efficiency to enhance gross margins. Lead a team of highly motivated individuals and encourage to develop new capabilities through learning and development and knowledge sharing initiatives Lead by example in analytics delivery and guide the team in data synthesis, modeling techniques and culling out actionable insights, implications, and recommendations to address clients business KPIs and /or identify opportunities Ability to attract and retain high calibre talent for the organization and clearly communicate the vision, goals, and objectives of the organization and guide others in linking their activities to the success of the organization. Work effectively with peer groups in sales & marketing, practice teams and enabling functions to drive higher value to add to clients. Participate in the sales process to scope client needs and consult the client to frame up solution and delivery approach. Contribute to the development of the capability through collateral demonstrating thought leadership and develop scalable solutions to address business problems across the industry Describe the role in detail without mentioning any technical tool/platform/programming language) Section 2 (Mandatory technical skills) 11+ years of experience in analytics delivery and business consulting with at least 5+ years of leadership experience along with 3+ years of experience in creating solutions for Marketing teams Experience in design and review of new solution concepts and leading the delivery of high-impact analytics solutions and programs for global clients. Knowledge of AI and machine learning techniques such as deep learning, neural networks, LLMs, Reasoning models to drive superior measurement techniques for the client. Should be able to evaluate and bring in new advanced techniques to enhance the value-add for clients Should be able to apply domain knowledge to functional areas like market size estimation, business growth strategy, impact of govt policies on product, strategic revenue management, marketing effectiveness Must have excellent project/program management skills and have experience managing multiple work streams and projects at one time Have business acumen to manage revenues profitably and meet financial goals consistently. Able to quantify business value for clients and create win-win commercial propositions. Good thought leadership & ability to structure & solve business problems, innovating, where required Outstanding presentation and communication skills (Oral and written) with the ability to inspire others to make informed decisions. Must have the ability to adapt to changing business priorities in a fast-paced business environment Post graduate degree in a quantitative discipline from a reputed institute

8-12 years of experience in a Product Management / Functional Engineering role. Expertise and deep understanding of the application of AI, Machine Learning and Deep Learning tools to solve real world problems at a scale. Experience working within Cloud, SaaS, emerging cloud use-cases for web/mobile and enterprise companies, or complex supply chain networks. Ability to prioritize work for scrum teams and manage changing priorities Demonstrated ability to achieve goals in an innovative and fast-paced environment and to evolve product strategy based on research, data and industry trends. Excellent problem-solving, organizational, analytical and influencing skills, with proven ability to take initiative and build strong, productive relationships.

We are seeking a highly experienced and strategic Senior Manager Applied Science to lead and scale our applied research and machine learning initiatives. This role involves working at the intersection of cutting-edge AI/ML technologies and real-world business challenges to drive measurable impact. Key Responsibilities: Lead a team of applied scientists and machine learning engineers to develop scalable AI/ML models. Define and drive the scientific vision, strategy, and roadmap aligned with business goals. Collaborate cross-functionally with product, engineering, and analytics teams. Stay ahead of emerging technologies and apply them to solve complex business problems. Publish research, file patents, or present findings in internal/external forums as needed. Requirements: 10+ years of experience in applied science, machine learning, or data science roles. Strong background in statistics, optimization, deep learning, NLP, or related fields. Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. Proven experience in leading high-performance technical teams. Advanced degree (Ph.D. or Master’s) in Computer Science, Mathematics, Statistics, or a related field. Excellent communication and leadership skills. Preferred Qualifications: Experience in a product-led tech company or research lab environment. Track record of deploying ML models in production. Publications or patents in relevant areas.

Role & responsibilities Develop, implement & fine-tune deep learning AI models for wide range of Computer Vision application including object classification, object detection, segmentation, OCR & NLP Perform data annotation using automation script & preprocessing to prepare high-quality datasets for training our in-house deep learning models. Training of AI models with model inference and evaluate model accuracy & performance metrics using frameworks like PyTorch, Tensorflow Collaborate with software engineers to deploy models in production systems, ensuring scalability, reliability and efficiency. Develop APIs using FastAPI or similar frameworks to enable seamless integration and interaction with deployed models Experience in Deep Learning, Computer Vision, NLP with a focus on object classification, detection, segmentation, OCR & text processing. Pytho , C++, Understanding of deep learning frameworks such as Tensorflow, PyTorc,h or Keras Experience with AI model training,hyperparameters tunin,g and evaluation of large-scale datasets. Data Annotation familiarity & preprocessing techniques to prepare datasets for deep learning models. Version control systems like Git Problem-solving skills, communication skills, collaboration skills, team player AI Model deployment & serving, including the use of APIs and frameworks like FastAPI

Key Responsibilities Provide strategic direction and technical leadership in applying machine learning/ AI within the organization, aligned with company goals and challenges. Influence R&D roadmap based on deep industry understanding and business needs. Drive innovation with novel solutions in the automotive industry, advancing applied science through latest research implementation. Act as a key liaison between R&D and stakeholders, ensuring technical alignment with business objectives. Collaborate with cross-functional teams to define and integrate machine learning solutions into products and services. Publish research in top conferences, advancing field knowledge. Provide mentorship to applied scientists, ensuring project success.Contribute to team growth through training and collaborative projects. Define metrics for model evaluation in offline and real-time settings. Quantify and communicate ML impact to executives, influencing decisions. Champion ethical AI practices, ensuring compliance and standards. Define best practices for ML model development, testing, validation, and monitoring. Demonstrate data-driven business acumen and technical expertise across development lifecycle. Maintain technical excellence in algorithm development and deployment. Required Qualifications Bachelors/ Masters / PhD in Data Science, Mathematics, Operations Research or related field. The right candidate has a background in probability and statistics, applied mathematics, or computational science and a history of solving difficult problems with good business impact using a scientific approach. Experience working with major ML algorithms and frameworks. Significant experience in Data Science and Machine Learning with a strong proven track record in delivering positive business impact. 11+ years of hands-on experience with analytics, data science and big data experience in a business context. Proficient in Machine Learning, Deep Learning and Explainable AI concepts with the ability to explain them clearly to non-technical audiences Experienced in developing and adapting state-of-the-art models for specific business needs, demonstrating a track record of success in complex, cross-functional projects. Utilizing Probability and Statistics to derive meaningful insights from data. Proficient in deep learning frameworks like TensorFlow, Keras, and PyTorch, and utilizing computer vision (OpenCV) and natural language processing (spaCy) libraries. Implementing deep learning techniques, particularly Neural Networks. Applying both fundamental and advanced Natural Language Processing concepts. Implementing Computer Vision methodologies. Experience with Large Language Models is a must. Should have fine-tuned LLM on domain dataset. Utilizing Git for efficient code management and version control. Leveraging cloud platforms such as Google Cloud Platform, Microsoft Azure, and Amazon Web Services. Should be well versed with Design of Experiments. Experience in programming with Python and SQL or similar languages. Experience in distributed model training. Proficient in data visualization and presentation, transforming complex analyses into actionable insights. Experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, Airflow). Experience using ML platforms such as Databricks and SageMaker. Preferred Qualifications Experience in Recommendation Engine, Natural Language Processing, Computer Vision Domain knowledge of automotive industry. Enjoys discovering and solving problems; proactively seeking clarification of requirements and direction; being a self-starter who takes responsibility when required. Familiarity with Spark Strong interpersonal, verbal, visual and presentation skills, ability to communicate complex findings in a simple manner to executives. Ability to work collaboratively across multiple products and application teams. A willingness to learn, share and improve.

So, what s the role all about NICE provides state-of-the-art enterprise level AI and analytics for all forms of business communications between speech and digital. We are a world class research team developing new algorithms and approaches to help companies with solving critical issues such as identifying their best performing agents, preventing fraud, categorizing customer issues, and determining overall customer satisfaction. If you have interacted with a major contact center in the last decade, it is very likely we have processed your call. The research group partners with all areas of NICE s business to scale out the delivery of new technology and AI models to customers around the world that are tailored to their company, industry, and language needs. How will you make an impact Conduct cutting-edge research and develop advanced NLP algorithms and models. Build and fine-tune deep learning and machine learning models, with a focus on large language models. Work closely with internal stakeholders to define model requirements and ensure alignment with business objectives. Develop AI predictive models and perform data and model accuracy analyses. Produce and present findings, technical concepts, and model recommendations to both technical and non-technical stakeholders. Develop and maintain scripts/tools to automate both new model production and updates to existing model packages. Stay abreast of the latest advancements in data science research and contribute to the development of our knowledge base. Collaborate with developers to design automation and tool improvements for model building. Maintain documentation of processes and projects across all supported languages and environments. Have you got what it takes Masters degree in the field of Computer Science, Technology, Engineering, Math, or equivalent practical experience Minimum of 4-7 years of data science work experience, including implementing machine learning and NLP models using real-life data. Strong research skills, with a proven track record of developing and implementing advanced machine learning algorithms. Advanced knowledge of supervised and unsupervised machine learning algorithms. Excellent proficiency in Python programming. Experience with deep learning models and libraries such as PyTorch, TensorFlow, Hands-on experience with transformer models and Gen AI frameworks (HuggingFace, AWS Bedrock, Azure Foundry ). Strong verbal and written communication skills, including effective presentation abilities. Ability to work independently and as part of a team, demonstrating analytical thinking and problem-solving skills. You will have an advantage if you also have: Experience deploying models in production environments, ensuring scalability and performance using AWS/GCP/Azure Familiarity with relational databases and query languages (e. g. , MSSQL) and basic SQL knowledge. Experience with Retrieval-Augmented Generation (RAG) pipelines Understanding of multimodal models (text, audio, vision). Experience in Customer Experience domains. Experience working on international, globe-spanning teams. Past participation in a formal research setting. Experience as part of a software organization What s in it for you Enjoy NICE-FLEX! Requisition ID : 7294 Reporting into : Tech Manager Role Type : Individual Contributor About NICE

Role –Senior Gen AI Engineer Location - Chennai - CKC Mode of Interview - In Person Data - 7th June 2025 (Saturday) Job Description: Collect and prepare data for training and evaluating multimodal foundation models. This may involve cleaning and processing text data or creating synthetic data. Develop and optimize large-scale language models like GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders) Work on tasks involving language modeling, text generation, understanding, and contextual comprehension. Regularly review and fine-tune Large Language models to ensure maximum accuracy and relevance for custom datasets. Build and deploy AI applications on cloud platforms – any hyperscaler Azure, GCP or AWS. Integrate AI models with our company's data to enhance and augment existing applications. Role & Responsibility Handle data preprocessing, augmentation, and generation of synthetic data. Design and develop backend services using Python or .NET to support OpenAI-powered solutions (or any other LLM solution) Develop and Maintaining AI Pipelines Work with custom datasets, utilizing techniques like chunking and embeddings, to train and fine-tune models. Integrate Azure cognitive services (or equivalent platform services) to extend functionality and improve AI solutions Collaborate with cross-functional teams to ensure smooth deployment and integration of AI solutions. Ensure the robustness, efficiency, and scalability of AI systems. Stay updated with the latest advancements in AI and machine learning technologies. Skills & Experience Strong foundation in machine learning, deep learning, and computer science. Expertise in generative AI models and techniques (e.g., GANs, VAEs, Transformers). Experience with natural language processing (NLP) and computer vision is a plus. Ability to work independently and as part of a team. Knowledge of advanced programming like Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models. Knowledge of Natural language processing (NLP) for text generation projects like text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models. Experience in Data management, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models. Experience in developing and deploying AI models in production environments. Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying , managing and scaling AI solutions Should be able to bring new ideas and innovative solutions to our clients

Job Summary Data scientist Co-ordinate tasks/deliverables within the team Apply data science techniques such as machine learning statistical modeling and artificial intelligence Responsibilities Technology SPOC responsible for solution design Work with the business and technical system client stakeholder to understand current application pains architecture. He will help in building the Architectural blue print Help to define/propose architectures tech stack. Help to define/propose the Machine Learning Algorithms and models. Manage a team of data scientists machine learning engineers Help the Project Manager with work breakdown structure and User Story definitions Co-ordinate tasks deliverables within the team Apply data science techniques such as machine learning statistical modeling and artificial intelligence Measure and improve results Present Final results to stake holders Primary skills: Data science Python AIML GEN AI NLP GCP stack Secondary skills: Pharmacy domain and Data engineering skills

Job description MLOps Engineer Bangalore (work at office) 5+ Years experience relevant in MLOPs Mandatory Skills: Strong proficiency in Generative AI, Large Language Models (LLMs), deep learning, agentic frameworks, and RAG setup. Experience in designing and implementing machine learning models using scikit-learn and TensorFlow. Hands-on expertise with AI/ML frameworks such as Hugging Face, LangChain, LangGraph, and PyTorch. Cloud AI services experience, particularly in AWS SageMaker and AWS Bedrock. MLOps & DevOps: Knowledge of data pipeline setup, Apache Airflow, CI/CD, and containerization (Docker, Kubernetes). API Development: Ability to develop and maintain APIs following RESTful principles. Technical proficiency in Elastic, Python, YAML, and system integrations. Nice to Have: Experience with Observability, Ansible, Terraform, Git, Microservices, AIOps, and scripting in Python. Familiarity with AI cloud services such as Azure OpenAI and Google Vertex AI.

Job Role : AI/ML Technical Project Manager Exp: 12-18 Years Work Location : Chennai / Hyderabad Work Model : Hybrid Role Summary: The AI Manager leads the AI team, contributing to technical strategy and decision-making. This role involves managing the day-to-day delivery of the AI/ML team, responsible for building, deploying, and maintaining robust, scalable, and efficient ML models. Essential Responsibilities: Provide technical leadership and strategic direction for the AI team, aligning with overall company objectives. Lead and mentor a team of data engineers, MLops engineers, and machine learning engineers to achieve project objectives and deliverables (development and deployment of ML models for AI use cases across the platform). Contribute to AI/ML architecture design and implementation. Collaborate with business, engineering, infrastructure, and data science teams to translate their needs or challenges into production-grade Artificial Intelligence and Machine Learning models for batch and real-time requirements. Serve as a primary point of contact for US & Thryve leaders, ensuring clear communication and aligning with project goals and objectives. Guide the AI/ML engineers with respect to business objectives, connecting the dots, and helping the team come up with optimal ML models based on use cases. Manage day-to-day operations, ensuring adherence to process, scope, quality, and timelines. Assume the role of an engagement coordinator between the Thryve India team and US counterparts (techno-functional). Highlight risks and concerns to the leadership team and work with multiple stakeholders to establish alignment, contingency, and/or mitigation plans as required. Proactively track delivery statuses and project progress, taking ownership of all deliverables from Thryve. Communicate effectively with team members, US stakeholders, and management. Stay up to date with the latest trends and advancements in AI and ML and identify opportunities for the team to implement new models and technologies. Propose and implement best engineering and research practices for scaling ML-powered features, enabling fast iteration and efficient experimentation with novel features. Required Skills and Qualifications: Bachelor's degree in engineering, computer science, or a related field. 12 to 18 years of total experience, with at least 2 years of experience leading/managing AI/ML projects with Predictive Modeling experience, achieving clear & measurable business objectives. Understanding of US Health insurance with at least 2+ years of experience in the same. Experience and understanding of the entire MLops pipeline, from data ingestion to production. Strong understanding of AI/ML concepts & algorithms, including supervised, unsupervised, and reinforcement learning, as well as MLops. Proven ability to take successful, complex ideas from experimentation to production. Hands-on experience with Google Cloud Platform (GCP) or any public cloud platform. Excellent communication, presentation, and interpersonal skills. Proven experience in leading, motivating & inspiring teams to foster collaboration. Proficient in identifying, assessing, and calling out risks and mitigation plans to stakeholders. Experience in implementing process improvements and learning from past projects to enhance future performance. Ability to analyze external and internal processes and create strategies for service delivery optimization. Experience in working with diverse teams and stakeholders, understanding their needs and managing expectations.

About Us: Founded in 2008, Red & White is Gujarats leading NSDC & ISO-certified institute, focused on industry-relevant education and global employability. Role Overview: Were hiring a faculty member to teach AI, Machine Learning, and Data Science. The role includes delivering lectures, guiding projects, mentoring students, and staying updated with tech trends. Key Responsibilities: Deliver high-quality lectures on AI, Machine Learning, and Data Science . Design and update course materials, assignments, and projects. Guide students on hands-on projects, real-world applications, and research work. Provide mentorship and support for student learning and career development. Stay updated with the latest trends and advancements in AI/ML and Data Science. Conduct assessments, evaluate student progress, and provide feedback. Participate in curriculum development and improvements. Skills & Tools: Core Skills: ML, Deep Learning, NLP, Computer Vision, Business Intelligence, AI Model Development, Business Analysis. Programming: Python, SQL (Must), Pandas, NumPy, Excel. ML & AI Tools: Scikit-learn (Must), XGBoost, LightGBM, TensorFlow, PyTorch (Must), Keras, Hugging Face. Data Visualization: Tableau, Power BI (Must), Matplotlib, Seaborn, Plotly. NLP & CV: Transformers, BERT, GPT, OpenCV, YOLO, Detectron2. Advanced AI: Transfer Learning, Generative AI, Business Case Studies. Education & Experience Requirements: Bachelor's/Masters/Ph.D. in Computer Science, AI, Data Science, or a related field. Minimum 1+ years of teaching or industry experience in AI/ML and Data Science. Hands-on experience with Python, SQL, TensorFlow, PyTorch, and other AI/ML tools. Practical exposure to real-world AI applications, model deployment, and business analytics. For further information, please feel free to contact 7862813693 us via email at career@rnwmultimedia.edu.in