515 Mlops Jobs - Page 4

As a Machine Learning Developer with 1 to 3+ years of experience, you will be an integral part of our innovative team dedicated to designing, developing, and deploying machine learning models and algorithms that power our products and solutions. Your responsibilities will include collaborating with cross-functional teams such as data scientists, software engineers, and product managers to create scalable and efficient machine learning solutions. Your duties will encompass various aspects of machine learning development, including designing, implementing, and optimizing machine learning models and algorithms to address complex business challenges. You will be involved in preprocessing and analyzing large datasets to ensure data quality, consistency, and relevance for training models. Additionally, feature engineering and model evaluation using appropriate metrics will be key components of your role. Collaboration with software engineers to deploy models into production environments, focusing on scalability and reliability, will be a crucial part of your responsibilities. Staying abreast of the latest advancements in machine learning, AI, and data science to implement cutting-edge techniques and tools will be essential. Furthermore, you will work closely with data scientists, software developers, and product teams to integrate machine learning capabilities into various products and services. Your required skills and qualifications include 1 to 3+ years of hands-on experience in machine learning, data science, or a related role, as well as a strong background in handling large datasets and familiarity with SQL and NoSQL databases. Experience in developing, training, and deploying machine learning models, including regression, classification, clustering, and deep learning techniques, is essential. Excellent verbal and written communication skills, the ability to work effectively in a team-oriented environment, and a passion for continuous learning and improvement are also crucial attributes. Knowledge of cloud platforms such as AWS, Google Cloud, or Azure, along with proficiency in natural language processing (NLP), computer vision, or reinforcement learning, will be beneficial. Familiarity with MLOps practices and tools for continuous integration and deployment of ML models is also desirable. This position is based in Indore, Madhya Pradesh, and requires on-site work at various locations in India and globally, including the USA, UK, Australia, and the Middle East. If you are enthusiastic about leveraging your machine learning expertise in a dynamic and collaborative environment, we encourage you to apply from the specified locations.,

As a Senior Generative AI Engineer, your primary role will involve conducting original research on generative AI models. You will focus on exploring model architecture, training methodologies, fine-tuning techniques, and evaluation strategies. It is essential to maintain a strong publication record in esteemed conferences and journals, demonstrating your valuable contributions to the fields of Natural Language Processing (NLP), Deep Learning (DL), and Machine Learning (ML). In addition, you will be responsible for designing and experimenting with multimodal generative models that incorporate various data types such as text, images, and other modalities to enhance AI capabilities. Your expertise will be crucial in developing autonomous AI systems that exhibit agentic behavior, enabling them to make independent decisions and adapt to dynamic environments. Leading the design, development, and implementation of generative AI models and systems will be a key aspect of your role. This involves selecting suitable models, training them on extensive datasets, fine-tuning hyperparameters, and optimizing overall performance. It is imperative to have a deep understanding of the problem domain to ensure effective model development and implementation. Furthermore, you will be tasked with optimizing generative AI algorithms to enhance their efficiency, scalability, and computational performance. Techniques such as parallelization, distributed computing, and hardware acceleration will be utilized to maximize the capabilities of modern computing architectures. Managing large datasets through data preprocessing and feature engineering to extract critical information for generative AI models will also be a crucial aspect of your responsibilities. Your role will also involve evaluating the performance of generative AI models using relevant metrics and validation techniques. By conducting experiments, analyzing results, and iteratively refining models, you will work towards achieving desired performance benchmarks. Providing technical leadership and mentorship to junior team members, guiding their development in generative AI, will also be part of your responsibilities. Documenting research findings, model architectures, methodologies, and experimental results thoroughly is essential. You will prepare technical reports, presentations, and whitepapers to effectively communicate insights and findings to stakeholders. Additionally, staying updated on the latest advancements in generative AI by reading research papers, attending conferences, and engaging with relevant communities is crucial to foster a culture of learning and innovation within the team. Mandatory technical skills for this role include strong programming abilities in Python and familiarity with frameworks like PyTorch or TensorFlow. In-depth knowledge of Deep Learning concepts such as CNN, RNN, LSTM, Transformers LLMs (BERT, GEPT, etc.), and NLP algorithms is required. Experience with frameworks like Langgraph, CrewAI, or Autogen for developing, deploying, and evaluating AI agents is also essential. Preferred technical skills include expertise in cloud computing, particularly with Google/AWS/Azure Cloud Platform, and understanding Data Analytics Services offered by these platforms. Hands-on experience with ML platforms like GCP: Vertex AI, Azure: AI Foundry, or AWS SageMaker is desirable. Strong communication skills, the ability to work independently with minimal supervision, and a proactive approach to escalate when necessary are also key attributes for this role. If you have a Master's or PhD degree in Computer Science and 6 to 8 years of experience with a strong record of publications in top-tier conferences and journals, this role could be a great fit for you. Preference will be given to research scholars from esteemed institutions like IITs, NITs, and IIITs.,

Key Responsibilities Strategic Leadership: Define and articulate the AI/ML vision and strategy for the company, ensuring alignment with overall business goals. Identify new opportunities to leverage AI/ML to drive innovation, efficiency, and revenue growth. Team Management & Mentorship: Lead, mentor, and grow a high-performing team of data scientists and machine learning engineers. Foster a culture of collaboration, innovation, and continuous learning. Provide technical guidance and career development support to team members. End-to-End Project Ownership: Oversee the entire lifecycle of AI/ML projects, from ideation and requirements gathering to model development, deployment, and monitoring. Ensure projects are delivered on time, within budget, and to the highest quality standards. Technical Architecture & Development: Provide hands-on technical leadership in the design and architecture of scalable and production-ready AI/ML solutions. Stay current with the latest advancements in the field and guide the team in adopting best practices for model development, MLOps, and data governance. Cross-Functional Collaboration: Work closely with product managers, software engineers, and business stakeholders to identify and prioritize AI/ML use cases. Effectively communicate complex technical concepts and project outcomes to both technical and non-technical audiences. Model Governance & Ethics: Establish and enforce standards for model validation, performance monitoring, and ethical AI. Ensure our models are fair, transparent, and compliant with relevant regulations. Required Skills & Qualifications Educational Background: Degree in Computer Science or Maths, Artificial Intelligence, Statistics, or a related quantitative field. Professional Experience: A minimum of 10 years of professional experience in data science and machine learning, with at least 3-4 years in a leadership or management capacity. Proven Expertise: Demonstrated experience in developing and deploying a wide range of machine learning models, including but not limited to deep learning (CNNs, RNNs, Transformers), natural language processing (NLP), computer vision, and reinforcement learning. Technical Proficiency: Expert-level programming skills in Python. Extensive experience with ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras. Strong experience with cloud platforms (AWS, Azure, or GCP) and their respective ML services (e.g., SageMaker, Azure ML, Vertex AI). Solid understanding of MLOps principles and tools (e.g., MLflow, Kubeflow, Docker, Kubernetes). Proficiency in data manipulation and analysis using SQL and libraries like Pandas and NumPy. Leadership Acumen: Proven ability to lead and inspire technical teams. Excellent project management, communication, and interpersonal skills. Preferred A portfolio of patents or publications in reputable AI/ML journals or conferences. Experience working in a fast-paced, agile environment. Familiarity with big data technologies like Apache Spark or Hadoop. Experience with building and scaling AI solutions for [mention your specific industry, e.g., FinTech, Healthcare, E-commerce].

Responsibilities Lead the development and implementation of advanced machine learning models and statistical analyses to solve complex business problems Collaborate with business stakeholders to understand requirements and translate them into analytical solutions Manage a team of business intelligence experts Work closely together with the technology teams in implementing new techniques into the Bank environments Develop predictive models for risk assessment, fraud detection, customer behavior analysis or forecasting Create and maintain detailed documentation of methodologies, models, and processes Design and build scalable data pipelines and ETL workflows Present findings and recommendations to senior management and stakeholders Monitor model performance and implement improvements as needed Ensure compliance with banking regulations and data governance policies Qualifications Education: Master's degree or Ph.D. in Data Science, Statistics, Computer Science, Mathematics, or related field Professional certifications in relevant technologies or methodologies are a plus Experience: 10+ years of experience in data science, with at least 4 years in the banking/financial services sector Proven track record of successfully implemented machine learning models in production Minimum 3 years of experience managing and leading data science teams Demonstrated experience in building and developing high-performing teams Technical Skills: Advanced knowledge of machine learning algorithms and statistical modeling Strong expertise in Python, R, or similar programming languages Proficiency in SQL and experience with big data technologies (Hadoop, Spark, Databricks) Experience with deep learning frameworks Knowledge of cloud platforms (AWS, Azure, or GCP) Expertise in data visualization tools (Tableau, Power BI, Qlik) Strong understanding of version control systems (Git) Experience with MLOps and model deployments Business Skills: Proven people management and leadership abilities Experience in resource planning and team capacity management Excellent problem-solving and analytical thinking abilities Strong communication and presentation skills Ability to translate complex technical concepts to non-technical stakeholders Experience in agile development methodologies Understanding of banking and financial services domain Domain Knowledge: Understanding of risk management, compliance, products and regulatory requirements in banking Knowledge of financial markets and instruments is a plus

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.

We are hiring an AI Solution Architect with 12-15 years of experience in software development and architecture, with deep expertise in AI/ML within the healthcare IT domain. This is a 12-month full-time onsite role based in Chennai or Hyderabad for an immediate joiner. The ideal candidate will possess strong experience in cloud platforms (GCP preferred), AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn), and compliance with healthcare industry standards (e.g., HIPAA). Youll be responsible for designing scalable AI solutions, leading cross-functional teams, mentoring developers, and driving end-to-end AI solution delivery using MLOps best practices.

Youll need to work closely with Data Scientists, Data Engineers, UI Engineers, Software Developers, and DevOps teams to design and implement end-to-end AI/GenAI solutions. You will: Be responsible for training, integrating, and deploying AI/GenAI/ML models in Azure/AWS ecosystem. Design and implement enterprise-quality AI/GenAI/ML applications. Optimize deployed models for performance, scalability, and efficiency. Debug and troubleshoot issues in AI/GenAI/ML pipelines and systems. Monitor model performance in production and retrain as necessary to maintain accuracy. Stay conversant with the latest trends, techniques, and tools in GenAI pipelines. Experiment with state-of-the-art methods and propose innovative solutions to complex problems. Excellent written and verbal communication skills required. Technical Skills: Excellent Python, PySpark, and SQL skills. Knowledge of GenAI stack is a big plus. Experience with Azure DevOps / AWS DevOps for ML projects, Databricks, CI/CD pipelines, and repositories. Experience with Azure/AWS MLOps/Kubeflow. Experience of training and deploying AI/GenAI/ML models into production environments and integrating them with existing systems. Knowledge of containerization tools like Docker, orchestration systems like Kubernetes, and inference platforms like Kserve / NVIDIA Triton. Knowledge of Azure / AWS ETL pipelines is a plus (but not mandatory). Soft Skills: Excellent written and verbal communication. Exceptional problem-solving and multitasking skills in a fast-paced environment. Experience Level: 8+ years of experience in ML Engineering.

Visionify is dedicated to leveraging the potential of Computer Vision and AI for various real-world applications. We are currently seeking a highly skilled, motivated, and enthusiastic Senior Computer Vision Engineer to play a crucial role in implementing our strategic plans. As a Senior Computer Vision Engineer at Visionify, you will be tasked with tackling cutting-edge challenges in the realm of Computer Vision by devising innovative algorithms and optimizations. The majority of our projects revolve around practical applications of Computer Vision, necessitating a strong grasp of contemporary model types such as Classification, Object detection, Object Recognition, OCR, LayoutML, and GAN networks. Proficiency in Pytorch is essential for this role, as it serves as our primary programming language. Familiarity with Azure and Azure ML Studio would be advantageous. Candidates applying for this position should remain abreast of the latest advancements and actively contribute to enhancing the Pytorch project's performance and accuracy. Your expertise in PyTorch and its underlying mechanisms will be pivotal in resolving customer challenges and offering valuable insights into product improvements. Experience in optimizing and streamlining models for deployment on edge devices, as well as converting models to NVIDIA TensorRT, will be highly valued. A strong foundation in Python programming is indispensable, given its widespread use in our organization for developing training and inference pipelines. Effective communication and presentation skills are also crucial. The ideal candidate will exhibit a deep passion for artificial intelligence and a commitment to staying updated on industry trends. **Responsibilities:** - Understanding business objectives and devising Computer Vision solutions that align with these goals, including developing training and inference frameworks and leveraging various ML technologies. - Building and optimizing Pytorch models for different runtime environments, including NVIDIA Jetson TensorRT. - Guiding the development team, addressing their queries, and facilitating the timely completion of their tasks. - Creating ML/Computer Vision algorithms to address specific challenges. - Analyzing and visualizing data to identify potential performance-affecting disparities in data distribution, especially when deploying models in real-world scenarios. - Establishing processes for core team operations, such as data acquisition, model training, and prototype development. - Identifying and utilizing open-source datasets for prototype building. - Developing pipelines for data processing, augmentation, training, inference, and active retraining. - Training models, fine-tuning hyperparameters, and devising strategies to address model errors. - Deploying models for production use. **Requirements:** - Bachelor's or Master's degree in Computer Science, Computer Engineering, IT, or a related field. - Minimum of 5 years of relevant experience; candidates with exceptional skills but less experience are encouraged to apply. - Industry experience in Image & Video Processing, including familiarity with OpenCV, GStreamer, TensorFlow, PyTorch, TensorRT, and various model training/inference techniques. - Proficiency in deep learning classification models (e.g., ResNet, Inception, VGG) and object detection models (e.g., MobileNetSSD, Yolo, FastRCNN, MaskRCNN). - Strong command of Pytorch, Torchvision, and the ability to develop training routines and update models effectively. - Familiarity with Colab, Jupyter Notebook, CUDA/GPU, and CNN visualization techniques like CAM and GradCAM. - Expertise in Computer Vision and real-time video processing methods. - Proficient in Python programming and adept at writing reusable code. - Experience with OpenCV, Scikit packages, NVIDIA platform tools (e.g., Deepstream, TensorRT), Python web frameworks (e.g., Flask, Django, FastAPI), and ML platforms (e.g., PyTorch, TensorFlow). - Knowledge of AWS SageMaker, various databases (e.g., Elasticsearch, SQL, NoSQL, Hive), cloud environments (preferably AWS) for software development, GPU-based training infrastructures, Docker, and DevOps and MLOps best practices for ML systems. **Desired Traits:** - Collaborative mindset and ability to thrive in a team environment. - Adaptability to evolving requirements. - Proclivity for innovative problem-solving. - Strong focus on work quality and developing robust code.,

Joining Gadgeon offers a dynamic and rewarding career experience that fosters both personal and professional growth. Our collaborative culture encourages innovation, empowering team members to contribute their ideas and expertise to cutting-edge projects. We are currently looking for a Computer Vision Engineer to join our team. The ideal candidate should have 3-4 years of experience and possess a strong background in image processing, deep learning, and machine learning techniques. Hands-on experience in developing and deploying computer vision applications is also required. As a Computer Vision Engineer at Gadgeon, your responsibilities will include: - Designing, developing, and optimizing computer vision algorithms for tasks such as object detection, tracking, segmentation, depth estimation, and activity recognition. - Implementing and training deep learning models using frameworks such as TensorFlow, PyTorch, and OpenCV. - Processing and analyzing large-scale image and video datasets to extract meaningful insights. - Developing and optimizing deep learning pipelines, including dataset preparation, model training, evaluation, and deployment. - Working with multiple camera inputs and multimodal data for real-time applications. - Collaborating with software engineers and data scientists to integrate computer vision models into production environments. - Researching and implementing the latest advancements in computer vision and deep learning. - Debugging and troubleshooting issues in vision-based applications, optimizing for accuracy and performance. - Working on AI infrastructure, machine learning accelerators, and on-device optimization. Required Qualifications: - B.Tech in Computer Science, Electrical Engineering, Electronics, or a related field. - Hands-on experience developing learning algorithms for computer vision tasks such as object detection, object tracking, segmentation, optical flow, and multi-view geometry. - Strong understanding of deep learning architectures, representational learning, and domain adaptation. - Ability to train, debug, and deploy deep learning models, iterating on failure characterization and model improvement. - Proficiency in Python and ML/DL frameworks such as TensorFlow, PyTorch, and TensorRT. - Experience working with multiple input sources such as cameras, LiDAR, and embedded controllers. - Hands-on experience with MLOps tools and methods is a plus. - Familiarity with AI infrastructure, machine learning accelerators, and on-device optimization. - Strong programming skills with experience in C++, Python, or C#. - Experience with version control tools such as Git and development in Linux environments. - Highly motivated individual with a strong work ethic, the ability to work independently, and adaptability to a fast-paced environment. Preferred Qualifications: - Experience in 3D computer vision, SLAM, or LiDAR processing. - Knowledge of adversarial and generative models. - Exposure to hardware acceleration and embedded AI deployment. - Strong understanding of software development best practices and performance optimization.,

As a Data Analytics Lead with 10 years of experience, you will be responsible for driving the organization-wide analytics strategy and fostering a data-driven decision-making culture. Your key responsibilities will include building dashboards, leading advanced data analysis, developing predictive models, and ensuring ethical data usage. To excel in this role, you should have a B.E./B.Tech in Computer Science or equivalent qualification. Industry preference is given to Manufacturing/Process/IT sectors. You should also possess expertise in tools such as Tableau, Power BI, and Looker, along with knowledge of machine learning and MLOps. Strong communication and leadership skills are essential for effectively executing your responsibilities. Join us in this dynamic role where you will have the opportunity to drive analytics initiatives, develop predictive models, and lead the organization towards data-driven decision-making.,

As an Amdocs Software Architect, you will be responsible for leading the architectural roadmap, providing architecture solutions throughout the software development lifecycle, and performing advanced software engineering tasks. You will have the autonomy to deliver technical objectives, make decisions based on extensive analysis, and offer technical expertise in software usage, functional, and non-functional aspects. Collaborating with software engineers and other architects, you will define and refine product structures to align with business needs and ensure seamless development, deployment, and maintenance. Additionally, you will work closely with customers and product line management to translate customer requirements into technical specifications, support and lead architectural decisions within product lines, and oversee projects while guiding software engineers on design decisions. Researching, evaluating, and prototyping new methodologies and technologies, you will drive process and tool improvements, all while gaining a deep understanding of customer contexts to inform technical choices. Key Responsibilities: - Extensive experience working with Various LLMs such as Lama, Gpt, and others - Hands-on experience in handling GenAI use cases - Expertise in developing Cloud Jobs for data ingestion for learnings - Establishing partnerships with project stakeholders to offer technical assistance in critical decisions - Development and implementation of Gen AI Use-cases in Live Production as per business/user requirements Technical Skills: Mandatory Skills: 1. Deep learning engineering expertise, particularly in MLOps 2. Strong NLP/LLM experience for text processing using LLM 3. Proficiency in Python & Terraform programming 4. Building backend applications using Python and deep learning frameworks 5. Deploying models and creating APIs (FAST API, FLASK API) 6. Experience working with GPUs 7. Working knowledge of Vector databases like Milvus, Azure Cognitive Search, Quadrant 8. Expertise in transformers and hugging face models such as llama, Mixtral AI, and embedding models Good to Have: 1. Knowledge and experience in Kubernetes, Docker 2. Cloud experience with VMs and Azure storage 3. Sound data engineering experience Behavioral Skills: - Excellent communication with clients and operational managers, actively listening and providing solutions - Strong problem-solving skills and ability to gather information effectively - Building strong relationships with clients, operational managers, and colleagues - Adaptability, prioritization, and ability to work under pressure to meet deadlines - Proactive thinking, anticipating problems, and offering innovative solutions - Effective presentation skills - Willingness to work extended hours when required,

You will need hands-on experience in converting SAS to Python, along with strong mathematics and statistics skills to excel in this role. Additionally, proficiency in AI-specific utilities like ChatGPT, Hugging Face Transformers, etc., is essential. Your ability to comprehend business requirements and derive use cases and solutions from structured/unstructured data will be crucial. Your responsibilities will include converting SAS to Python code, acquiring the necessary skills for building and deploying machine learning models for production, and engaging in feature engineering, exploratory data analysis, pipeline creation, model training, and hyperparameter tuning. You will also be expected to develop and deploy cloud-based applications, such as LLM/GenAI, into production. Proficiency in programming languages like SAS, Python, Scikit-Learn, TensorFlow, PyTorch, Keras, and expertise in exploratory data analysis, machine learning, deep learning algorithms, model building, hyperparameter tuning, and model performance metrics are required. Knowledge of MLOps, data pipelines, data engineering, statistics, time series modeling, forecasting, image/video analytics, and natural language processing (NLP) will also be advantageous. Experience with ML services from cloud platforms like AWS, GCP, Azure, and Databricks is preferred. Basic knowledge of Databricks and Big Data, including Spark and Hive, is considered an asset. If you are looking to join a dynamic team and work in locations such as Indore, Noida, Gurgaon, Bangalore, or Pune, please share your profiles with details on notice period and compensation.,

You are a highly skilled Lead Backend Engineer with 7-10 years of experience, possessing a strong command over Java and Python along with a deep understanding of GenAI and Large Language Models (LLMs). At Team Geek Solutions, we are innovators driven by cutting-edge technology, aiming to solve real-world problems using scalable backend systems and next-gen AI. Our collaborative and forward-thinking culture values every engineer's role in building impactful products. As a Lead Backend Engineer, you will be responsible for leading a team of developers and data scientists to design scalable backend architectures and AI-driven solutions, leveraging the latest advancements in AI capabilities. Your key responsibilities will include leading and mentoring a team of backend and AI engineers, architecting and developing robust backend solutions using Java and Python, solving complex problems using structured and unstructured data, and implementing state-of-the-art LLMs such as OpenAI and HuggingFace models. You will also be involved in utilizing techniques like Retrieval-Augmented Generation (RAG) to enhance the performance and capabilities of LLM-based systems, as well as owning the development of end-to-end ML pipelines encompassing training, fine-tuning, evaluation, deployment, and monitoring (MLOps). Collaboration with business and product teams to identify use cases and deliver AI-powered solutions is another crucial aspect of your role. The required skills for this position include proficiency in Java and Python, a solid understanding of Data Structures & Algorithms, deep experience in Transformer-based models, LLM fine-tuning, and deployment, hands-on experience with PyTorch, LangChain, and Python web frameworks such as Flask and FastAPI, strong database skills with SQL, and experience in deploying and managing ML models in production environments. Leadership experience in managing small to mid-sized engineering teams is also essential. Preferred or good-to-have skills for this role include experience with LLMOps tools and techniques, exposure to cloud platforms like AWS, GCP, or Azure for model deployment, strong written and verbal communication skills for both technical and non-technical audiences, and a passion for innovation and building AI-first products. Keeping yourself updated with the latest advancements in AI and integrating best practices into development workflows will be a key aspect of your role at Team Geek Solutions.,

You are a talented and motivated Machine Learning Developer with 1 to 3+ years of experience, seeking to join an innovative team. In this role, you will be responsible for designing, developing, and deploying machine learning models and algorithms that power products and solutions. Your collaboration with cross-functional teams, including data scientists, software engineers, and product managers, will be crucial in creating scalable and efficient machine learning solutions. Your duties and responsibilities will include designing, implementing, and optimizing machine learning models to solve complex business problems. You will preprocess and analyze large datasets, ensuring data quality and relevancy for model training. Feature engineering to enhance model accuracy, evaluating model performance, deploying models into production environments, and staying updated with the latest advancements in machine learning will be part of your responsibilities. Additionally, you will collaborate with various teams to integrate machine learning capabilities into products and services while maintaining comprehensive documentation for models and processes. To excel in this role, you should have 1 to 3+ years of hands-on experience in machine learning or data science, proficiency in handling large datasets and SQL/NoSQL databases, and expertise in developing, training, and deploying machine learning models. Strong communication skills, the ability to work effectively in a team environment, and experience with cloud platforms like AWS, Google Cloud, or Azure are essential. Knowledge of natural language processing, computer vision, reinforcement learning, and familiarity with MLOps practices will be advantageous. This position is based in Indore, MP, with a work-from-office model. However, you should be willing to work on-site at various locations in India and globally, including the USA, UK, Australia, and the Middle East, with on-site benefits applicable. Apply now if you are ready to contribute your skills and expertise to a dynamic and collaborative team environment.,

Techvantage.ai is a next-generation technology and product engineering company at the forefront of innovation in Generative AI, Agentic AI, and autonomous intelligent systems. We create intelligent, user-first digital products that redefine industries through the power of AI and engineering excellence. We are looking for a Senior Software Engineer-AI with 4-6 years of hands-on experience in Artificial Intelligence/ML and a passion for innovation. This role is ideal for someone who thrives in a startup environment, fast-paced, product-driven, and full of opportunities to make a real impact. You will contribute to building intelligent, scalable, and production-grade AI systems, with a strong focus on Generative AI and Agentic AI technologies. As a Senior Software Engineer-AI at Techvantage.ai, you will be responsible for building and deploying AI-driven applications and services, focusing on Generative AI and Large Language Models (LLMs). You will design and implement Agentic AI systemsautonomous agents capable of planning and executing multi-step tasks. Collaborate with cross-functional teams including product, design, and engineering to integrate AI capabilities into products. Write clean, scalable code and build robust APIs and services to support AI model deployment. Own feature delivery end-to-endfrom research and experimentation to deployment and monitoring. Stay current with emerging AI frameworks, tools, and best practices and apply them in product development. Contribute to a high-performing team culture and mentor junior team members as needed. In order to excel in this role, we are seeking candidates with 3-6 years of overall software development experience, with at least 3 years specifically in AI/ML engineering. Strong proficiency in Python is required, along with hands-on experience in PyTorch, TensorFlow, and Transformers (Hugging Face). Proven experience working with LLMs (e.g., GPT, Claude, Mistral) and Generative AI models (text, image, or audio) is highly desirable. Practical knowledge of Agentic AI frameworks (e.g., LangChain, AutoGPT, Semantic Kernel) is a plus. Experience building and deploying ML models to production environments is essential. Familiarity with vector databases (Pinecone, Weaviate, FAISS) and prompt engineering concepts is beneficial. Comfortable working in a startup-like environment is crucialself-motivated, adaptable, and willing to take ownership. A solid understanding of API development, version control, and modern DevOps/MLOps practices is expected from the ideal candidate.,

As a Senior Data Scientist, you will utilize your extensive experience and expertise in AI/ML technologies to drive innovation and solve real-world problems. Your responsibilities will include designing, developing, and optimizing recommendation systems to enhance user experience, building advanced NLP chatbots for automating customer interactions, leading Generative AI solutions, and applying Large Language Models like GPT and BERT to create innovative business-specific solutions. Collaboration with cross-functional teams is key as you integrate machine learning models into production systems, perform data exploration and feature engineering, and stay updated on the latest advancements in AI and ML technologies. Mentoring junior data scientists and engineers, collaborating with product managers and business stakeholders, and ensuring ethical and responsible model development are also crucial aspects of this role. To excel in this position, you should have 5+ years of experience in data science or machine learning, with strong expertise in recommendation systems, chatbots, Generative AI, and Large Language Models. Proficiency in machine learning frameworks like TensorFlow and PyTorch, as well as experience with cloud platforms and data pipelines, will be essential. Your problem-solving skills, statistical knowledge, and ability to convey technical concepts to non-technical stakeholders will further contribute to your success in this role. Joining our rapidly growing product-based company will provide you with the opportunity to collaborate with a talented team, work on high-quality software solutions, and enjoy a competitive compensation and benefits package. If you are passionate about AI/ML technologies and eager to make a significant impact, this role offers an exciting and rewarding career opportunity.,

As a Senior AI Engineer (Tech Lead) at EY, you will have the opportunity to leverage your technical expertise to develop and implement cutting-edge AI solutions. With a minimum of 4 years of experience in Data Science and Machine Learning, including NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture, you will play a crucial role in driving innovation and creating impactful solutions for enterprise industry use cases. Your responsibilities will include contributing to the design and implementation of state-of-the-art AI solutions, leading a team of 4-6 developers, and collaborating with stakeholders to identify business opportunities and define AI project goals. You will stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. By utilizing generative AI techniques, such as LLMs and Agentic Framework, you will develop innovative solutions tailored to specific business requirements. Your role will also involve integrating with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to enhance generative AI capabilities. Additionally, you will be responsible for implementing and optimizing end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Your expertise in data engineering, DevOps, and MLOps practices will be valuable in curating, cleaning, and preprocessing large-scale datasets for generative AI applications. To excel in this role, you should hold a Bachelor's or Master's degree in Computer Science, Engineering, or a related field, and demonstrate proficiency in Python, Data Science, Machine Learning, OCR, and document intelligence. Strong collaboration with software engineering and operations teams, along with excellent problem-solving and analytical skills, will be essential in translating business requirements into technical solutions. Moreover, your familiarity with trusted AI practices, data privacy, security, and ethical considerations will ensure the fairness, transparency, and accountability of AI models and systems. Additionally, having a solid understanding of NLP techniques, frameworks like TensorFlow or PyTorch, and cloud platforms such as Azure, AWS, or GCP will be beneficial in deploying AI solutions in a cloud environment. Proficiency in designing or interacting with agent-based AI architectures, implementing optimization tools and techniques, and driving DevOps and MLOps practices will also be advantageous in enhancing the performance and efficiency of AI models. Join EY to build an exceptional experience for yourself and contribute to creating a better working world for all through the power of AI and technology.,

Design and deploy AI-powered automation workflows. Build ML/NLP models, create scalable APIs, integrate with CRMs/ERPs, and lead end-to-end AI solution delivery in production.

Role Details: Position: AI Lead Location: Hyderabad, Telangana, India Key Responsibilities: Spearhead the end-to-end development, deployment, and continuous optimization of cutting-edge AI/ML systemsGenerative AI, LLMs/MLLMs, RAG, autonomous agents, and custom MCP servers in production Architect and implement scalable Retrieval-Augmented Generation pipelines, multi-modal transformer systems, and autonomous multi-agent frameworks (LangChain, AutoGPT, BabyAGI, NVIDIA NeMo Agents) Lead deep-learning model design and delivery: ANN, CNN, RNN, LSTM/BiLSTM, attention-based Transformers (BERT, GPT, T5, Vision Transformers), GANs, VAEs, Diffusion models, and Mixture-of-Experts architectures Define and enforce best practices for prompt engineering, fine-tuning (LlamaIndex, Hugging Face), quantization (INT4, GGUF), pruning, distillation, and advanced inference optimizations Build and maintain robust MLOps pipelines: CI/CD (Git, Bitbucket, automated tests), model versioning (MLflow, Hugging Face Hub & LFS), Docker/GPU containerization, Kubernetes/OpenShift orchestration, Terraform infrastructure as code Design high-performance data engineering workflows: ETL optimization (Pandas, NumPy, Spark), real-time streaming (Kafka, RabbitMQ), and caching strategies (Redis) Ensure secure, compliant AI deployments by embedding Responsible AI principles (bias mitigation, transparency, privacy), governance frameworks, and regulatory controls. Monitor emerging research (self-supervised pre-training, federated learning, synthetic data, LLMOps) and integrate top innovations into production Collaborate closely with Product, DevOps, Data Engineering, and Security teams; mentor and guide engineers and data scientists in software engineering and model validation best practices Required Qualifications: Education: Masters or PhD in AI/ML, Computer Science (AI/ML specialization), Data Science, Mathematics, or related field Industry Experience: 15+ years in AI/ML roles, including 710 years hands-on in Generative AI and Deep Learning, plus 5+ years in senior or leadership positions Hands-On Coding & Deployment: Expert at architecting, writing, debugging, deploying, and optimizing production-grade AI/ML code in Python (primary), C++, R, Java/Spring Boot, with strong testing, code-review, and performance-profiling discipline Deep Learning & Generative AI Frameworks: Advanced usage of PyTorch, TensorFlow, ONNX, GGUF, Hugging Face Transformers & Diffusers; fine-tuning pipelines (LlamaIndex, custom scripts) Large Language & Multimodal Models: Production deployment of LLMs, Multimodal LLMs (vision-language models, cross-modal understanding), RAG systems, and custom MCP A2A servers; embedding management & vector search with Pinecone, Milvus, Chroma, Quadrant Advanced Model Optimization: Quantization, pruning, distillation, MoE routing, efficient inference strategies, prompt-engineering platforms (LangSmith, PromptFlow) Classical & Advanced ML: Proficiency in regression, decision trees, random forests, SVM; boosting (XGBoost, CatBoost, LightGBM); clustering (K-Means, DBSCAN, hierarchical); RL (Q-Learning, DDPG, PPO); statistical methods and optimization math Computer Vision & Document Processing: Expertise in OpenCV, PyMuPDF, python-docx/pptx, pytesseract for advanced text/image extraction and analysis Cloud & Infrastructure: GPU acceleration (CUDA, cuDNN); AWS (Bedrock, SageMaker), Azure AI Studio & GPU Containers, GCP (Vertex AI, Cloud Run), serverless AI, NVIDIA Triton Inference Server Backend & APIs: FastAPI, OpenAPI, Django REST Framework, Flask for building and scaling AI microservices Data Engineering & Storage: ETL pipelines, streaming, caching; relational (MySQL, Oracle SQL), NoSQL (MongoDB), vector DBs MLOps & Observability: MLflow, Kubeflow; Docker, Kubernetes, OpenShift; CI/CD (Git, Bitbucket); monitoring with Prometheus, Grafana, OpenTelemetry, Logstash, Kibana Security & Compliance: Secure coding, network security, and adherence to GDPR, HIPAA, GxP standards Industry Certifications & Research: Must hold at least one recognized AI/ML certification (e.g. AWS Certified Machine Learning – Specialty, Google Professional Machine Learning Engineer, Microsoft Certified: Azure AI Engineer Associate) and have published research papers in top-tier AI/ML conferences or journals (NeurIPS, ACM, arXiv, AAAI, JMLR). Good to Have Skills: PhD-level publications and advanced certifications (Stanford AI, MIT, AWS, Google) Experience with federated learning, synthetic data generation, privacy-preserving ML (differential privacy, homomorphic encryption), and edge/in-device inference (TensorFlow Lite, CoreML) Familiarity with Responsible AI toolkits, model cards/DataCard’s, and AI risk management frameworks Significant open-source contributions to major AI/ML projects Proven success integrating AI in regulated industries (Texting/Messaging, pharma, healthcare, finance) Industries and disciplines. How to Apply: If you are a passionate developer who loves coding and thrives in an innovative startup environment, apply now to join our journey in revolutionizing communication! Apply here or email to join@beetexting.com

We are looking for a Data Scientist who will support building AI tools for customers The candidate should be skilled at using large data sets to find opportunities for product and process optimization The candidate must have a proven ability to drive business results with their databased insights The candidate must be comfortable working with a wide range of stakeholders and functional teams Primary Skills Python, AI, ML (Machine Learning) Gen AI Generative AI + RAG, NLP, LLM, Deep Learning, Computer Vision, AWS, Cloud Or Azure Open AI (Any Cloud) Experience- 5 to 16 Years Location - Pune If anyone is interested please share your updated resume on my email id - Devyani.Pillai2@ltimindtree.com

Mandatory Skills & Experience : - Expertise in designing and optimizing machine-learning operations, with a preference for LLM Ops. - Proficient in Data Science, Machine Learning, Python, SQL, Linux/Unix shell scripting. - Experience on Large Language Models and Natural Language Processing (NLP), and experience with researching, training, and fine-tuning LLMs. - Contribute towards fine-tune Transformer models for optimal performance in NLP tasks, if required. - Implement and maintain automated testing and deployment processes for machine learning models w.r.t LLMOps. - Implement version control, CI/CD pipelines, and containerization techniques to streamline ML and LLM workflows. - Develop and maintain robust monitoring and alerting systems for generative AI models ensuring proactive identification and resolution of issues. - Research or engineering experience in deep learning with one or more of the following : generative models, segmentation, object detection, classification, model optimisations. - Experience implementing RAG frameworks as part of available-ready products. - Experience in setting up the infrastructure for the latest technology such as Kubernetes, Serverless, Containers, Microservices etc. - Experience in scripting/programming to automate deployments and testing, working on tools like Terraform and Ansible. - Scripting languages like Python, bash, YAML etc. - Experience on CI/CD opensource and enterprise tool sets such as Argo CD, and Jenkins (others like Jenkins X, Circle CI, Argo CD, Tekton, Travis, Concourse an advantage). - Experience with the GitHub/DevOps Lifecycle. - Experience in Observability solutions (Prometheus, EFK stacks, ELK stacks, Grafana, Dynatrace, AppDynamics). - Experience in at-least one of the clouds for example Azure/AWS/GCP. - Significant experience on microservices-based, container-based or similar modern approaches of applications and workloads. - You have exemplary verbal and written communication skills (English). - Able to interact and influence at the highest level, you will be a confident presenter and speaker, able to command the respect of your audience. Desired Skills & Experience : - Bachelor level technical degree or equivalent experience; Computer Science, Data Science, or Engineering background preferred; Master's Degree desired. - Experience in LLM Ops or related areas, such as DevOps, data engineering, or ML infrastructure. - Hands-on experience in deploying and managing machine learning and large language model pipelines in cloud platforms (i.e., AWS, Azure) for ML workloads. - Familiar with data science, machine learning, deep learning, and natural language processing concepts, tools, and libraries such as Python, TensorFlow, PyTorch, NLTK etc. - Experience in using retrieval augmented generation and prompt engineering techniques to improve the model's quality and diversity to improve operations efficiency. - Proven experience in developing and fine-tuning Language Models (LLMs). - Stay up-to-date with the latest advancements in Generative AI, conduct research, and explore innovative techniques to improve model quality and efficiency. - The perfect candidate will already be working within a System Integrator, Consulting or Enterprise organisation with 8+ years of experience in a technical role within the Cloud domain. - Deep understanding of core practices including SRE, Agile, Scrum, XP and Domain Driven Design. - Familiarity with the CNCF open-source community. - Enjoy working in a fast-paced and dynamic environment using the latest technologies.

The AI Engineer with GenAI expertise is responsible for developing advanced technical solutions, integrating cutting-edge generative AI technologies. This role requires a deep understanding of modern technical and cloud-native practices, AI, DevOps, and machine learning technologies, particularly in generative models. You will support a wide range of customers through the "Ideation to MVP" journey, demonstrating proficiency in leading projects and ensuring delivery excellence. Key Responsibilities : Technical & Engineering Leadership : - Develop solutions leveraging GenAI technologies, integrating advanced AI capabilities into cloud-native architectures to enhance system functionality and scalability. - Lead the design and implementation of GenAI-driven applications, ensuring seamless integration with microservices and container-based environments. - Create solutions that fully leverage the capabilities of modern microservice and container-based environments running in public, private, and hybrid clouds. - Contribute to HCL thought leadership across the Cloud Native domain with an expert understanding of open-source technologies (i.e., Kubernetes/CNCF) and partner technologies. - Collaborate on joint technical projects with partners, including Google, Microsoft, AWS, IBM, Red Hat, Intel, Cisco, and Dell/VMware. Mandatory Skills & Experience. : - A passionate developer with 7+ years of experience in Java, Python, and Kubernetes, comfortable working as part of a paired/balanced team. - Extensive experience in software development, with significant exposure to AI/ML technologies. - Expertise in GenAI frameworks : Proficient in using GenAI frameworks and libraries such as LangChain, OpenAI API, and Hugging Face Transformers. - Prompt engineering : Experience in designing and optimizing prompts for various AI models to achieve desired outputs and improve model performance. - Strong understanding of NLP techniques and tools, including tokenization, embeddings, transformers, and language models. - Proven experience developing complex solutions that leverage cloud-native technologies-featuring container-based, microservices-based approaches; based on applying 12-factor principles to application engineering. - Exemplary verbal and written communication skills (English). - Positive and solution-oriented mindset. - Solid experience delivering Agile and Scrum projects in a Jira-based project management environment. - Proven leadership skills and the ability to lead projects to ensure delivery excellence. Desired Skills & Experience : - Machine Learning Operations (MLOps) : Experience in deploying, monitoring, and maintaining AI models in production environments using MLOps practices. - Data engineering for AI : Skilled in data preprocessing, feature engineering, and creating pipelines to feed AI models with high-quality data. - AI model fine-tuning : Proficiency in fine-tuning pre-trained models on specific datasets to improve performance for specialized tasks. AI ethics and bias mitigation : - Knowledgeable about ethical considerations in AI and experienced in implementing strategies to mitigate bias in AI models. Knowledgeable about vector databases, LLMs, and SMLs, and integrating with such models. - Proficient with Kubernetes and other cloud-native technologies, including experience with commercial Kubernetes distributions (e., Red Hat OpenShift, VMware Tanzu, Google Anthos, Azure AKS, Amazon EKS, Google GKE). - Deep understanding of core practices including DevOps, SRE, Agile, Scrum, Domain-Driven Design, and familiarity with the CNCF open-source community. - Recognized with multiple cloud and technical certifications at a professional level, ideally including AI/ML specializations from providers like Google, Microsoft, AWS, Linux Foundation, IBM, or Red Hat. Verifiable Certification : At least one recognized cloud professional / developer certification (AWS/Google/Microsoft).

House of Shipping is seeking a high-caliber Data Science Lead to join their team in Hyderabad. With a background of 15-18 years in data science, including at least 5 years in leadership roles, the ideal candidate will have a proven track record in building and scaling data science teams in logistics, e-commerce, or manufacturing. Strong expertise in statistical learning, ML architecture, productionizing models, and impact tracking is essential for this role. As the Data Science Lead, you will be responsible for leading enterprise-scale data science initiatives in supply chain optimization, forecasting, network analytics, and predictive maintenance. This position requires a blend of technical leadership and strategic alignment with various business units to deliver measurable business impact. Key responsibilities include defining and driving the data science roadmap across forecasting, route optimization, warehouse simulation, inventory management, and fraud detection. You will work closely with engineering teams to architect end-to-end pipelines, from data ingestion to API deployment. Proficiency in Python and MLOps tools like Scikit-Learn, XGBoost, PyTorch, MLflow, Vertex AI, or AWS SageMaker is crucial for success in this role. Collaboration with operations, product, and technology teams to prioritize AI use cases and define business metrics will be a key aspect of the job. Additionally, you will be responsible for managing experimentation frameworks, mentoring team members, ensuring model validation, and contributing to organizational data maturity. The ideal candidate will possess a Bachelor's, Master's, or Ph.D. degree in Computer Science, Mathematics, Statistics, or Operations Research. Certifications in Cloud ML stacks, MLOps, or Applied AI are preferred. To excel in this role, you should have a strategic vision in AI applications across the supply chain, strong team mentorship skills, expertise in statistical and ML frameworks, and experience in MLOps pipeline management. Excellent business alignment and executive communication skills are also essential for this position. If you are a data science leader looking to make a significant impact in the logistics industry, we encourage you to apply for this exciting opportunity with House of Shipping.,