66 Mlops Tools Jobs

Role Overview: You will play a crucial role in identifying and incubating cutting-edge AI technologies that align with the strategic goals of the company. Your responsibilities will include enhancing capabilities in data-driven decision-making, defining and promoting best practices in AI model development and deployment, and ensuring seamless integration of innovative AI solutions into existing frameworks tailored to meet the unique demands of the pharmaceutical industry. Your contribution will advance healthcare through technology, ultimately improving patient outcomes and driving business success. Key Responsibilities: - Understand complex and critical business problems, formulate integrated analytical approaches, employ statistical methods and machine learning algorithms to contribute to solving unmet medical needs, discover actionable insights, and automate processes for reducing effort and time for repeated use. - Architect and develop end-to-end AI/ML and Gen AI solutions with a focus on scalability, performance, and modularity while ensuring alignment and best practices with enterprise architecture standards. - Manage the implementation and adherence to the overall data lifecycle of enterprise data, enabling the availability of useful, clean, and accurate data throughout its useful lifecycle. - Work across various business domains, integrate business presentations, smart visualization tools, and contextual storytelling to translate findings back to business users with a clear impact. - Independently manage budget, ensuring appropriate staffing and coordinating projects within the area. - Collaborate with globally dispersed internal stakeholders and cross-functional teams to solve critical business problems and deliver successfully on high visibility strategic initiatives. Qualifications Required: - Advanced degree in Computer Science, Engineering, or a related field (PhD preferred). - 5+ years of experience in AI/ML engineering with at least 2 years focusing on designing and deploying LLM-based solutions. - Strong proficiency in building AI/ML architectures and deploying models at scale with experience in cloud computing platforms such as AWS, Google Cloud, or Azure. - Deep knowledge of LLMs and experience in applying them in business contexts. - Knowledge of containerization technologies (Docker, Kubernetes) and CI/CD pipelines. - Hands-on experience with cloud platforms (AWS, Azure, GCP) and MLOps tools for scalable deployment. - Experience with API development, integration, and model deployment pipelines. - Strong problem-solving skills, proactive hands-on approach to challenges, and ability to work effectively in cross-functional teams. - Excellent organizational skills and attention to detail in managing complex systems.,

As a Lead Software Engineer Machine Learning, your role will involve driving the design, development, and deployment of advanced machine learning solutions. You will need to showcase strong leadership skills, deep technical expertise, and the ability to guide teams in solving complex, large-scale problems using cutting-edge ML technologies. Your responsibilities will include defining and leading the strategy and roadmap for ML systems and applications, architecting scalable machine learning systems, and collaborating with cross-functional teams to identify ML use cases and requirements. Mentoring junior engineers, monitoring and improving the performance of machine learning systems, and leading research initiatives for emerging ML techniques will also be part of your role. **Key Responsibilities:** - Define and lead the strategy and roadmap for ML systems and applications. - Architect and oversee the development of scalable machine learning systems and infrastructure. - Drive the design and implementation of advanced ML models and algorithms. - Collaborate with cross-functional teams to identify ML use cases and requirements. - Mentor and guide junior engineers in best practices for ML development. - Monitor, evaluate, and improve the performance of machine learning systems. - Lead research initiatives to explore emerging ML techniques. **Qualifications Required:** - Bachelors or Masters degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field. A Ph.D. is a plus. - 10+ years of experience in software engineering, with at least 5 years focusing on machine learning. - Proficiency in ML frameworks and libraries like TensorFlow, PyTorch, and scikit-learn. - Strong expertise in designing and building large-scale, distributed ML systems. - Advanced knowledge of data engineering tools and frameworks, such as Spark, Hadoop, or Kafka. - Hands-on experience with cloud platforms (AWS, GCP, Azure) for ML workloads. - Expertise in deploying and managing ML models in production environments using MLOps tools like MLflow or Kubeflow. - Deep understanding of algorithms, data structures, and system design. - Experience with containerization (Docker) and orchestration (Kubernetes). The company is looking for a Lead Software Engineer Machine Learning with 10+ years of experience in data engineering or related fields. Strong leadership, problem-solving, and analytical thinking skills, along with excellent communication abilities, are essential for this role. You should also have the ability to foster collaboration, drive innovation, and effectively convey technical concepts to both technical and non-technical audiences.,

As a Generative AI Architect at NiCE, you will be responsible for providing technical leadership and architectural direction for the development and integration of Generative AI solutions within the organization's product portfolio and platform. Your role will involve collaborating closely with engineering, data science, product, and business stakeholders to ensure effective design, scalability, security, and operationalization of GenAI-powered features and systems. **Key Responsibilities:** - Set the end-to-end technical direction for Generative AI initiatives, including platform, technology stack, tools, and infrastructure. - Architect, design, and oversee the implementation of GenAI models and pipelines for production use cases. - Collaborate with cross-functional teams to define requirements, deliver functional and design specifications, and ensure alignment with business objectives. - Ensure that Generative AI solutions are scalable, secure, reliable, and maintainable, adhering to enterprise standards and best practices. - Lead architectural and design reviews for GenAI features and help establish coding and model development standards. - Evaluate, select, and integrate third-party GenAI platforms, frameworks, APIs, and cloud services as appropriate. - Drive continuous innovation by staying up-to-date with advances in GenAI, ML, and AI infrastructure. - Foster a culture of engineering excellence, mentoring team members on AI/ML, MLOps, and responsible AI practices. - Ensure robust model monitoring, performance evaluation, and feedback loops for deployed GenAI systems. - Collaborate with security and compliance teams to ensure adherence to data governance, privacy, and AI ethics requirements. - Contribute to strategic planning for AI initiatives and the company's long-term technology roadmap. - Mentor teams on the importance of each MCP pillar and drive adoption of best practices throughout the AI development lifecycle. **Qualifications:** - 15+ years of software development or technical leadership experience, with at least 5 years focused on AI/ML solutions and a minimum of 2 years architecting Generative AI systems. - Expertise in designing and deploying production-grade Generative AI solutions, including LLMs, summary generation, prompt engineering, and RAG-based architectures. - Experience with leading AI/ML frameworks and MLOps tools. - Strong understanding of cloud platforms and AI services. - Deep knowledge of machine learning concepts, data engineering, and model operationalization at scale. - Familiarity with responsible AI practices, including data privacy, fairness, explainability, and compliance. - Proficient in programming languages such as Python, Java, or similar; experience with containerization and orchestration. - Experience driving Continuous Integration and Delivery for AI/ML solutions. - Excellent problem-solving, decision-making, and communication skills. - Proven ability to mentor engineers and data scientists, foster teamwork, and drive consensus. - Experience working in Agile development environments. - Strong quality orientation, attention to detail, and ability to translate ideas into robust solutions. - Familiarity with security technologies and best practices for AI-enabled platforms. - Experience with AI/ML testing, monitoring, and continuous model evaluation in production. - Exposure to natural language processing (NLP) and computer vision applications. - Familiarity with MCP framework. - Passion for delivering innovative, high-quality GenAI products and platforms. - Ability to work independently and collaboratively across multi-disciplinary teams. - Demonstrated leadership in adopting new technologies and driving organizational change. - Strong customer orientation and ability to communicate complex technical concepts to non-technical stakeholders. - Commitment to ethical AI and continuous learning. NiCE offers a challenging work environment, competitive compensation, and benefits, and rewarding career opportunities. Join the NiCE team and be part of a fast-growing, highly respected organization where innovation and growth are at the forefront. Enjoy NiCE-FLEX hybrid model, combining office and remote work for maximum flexibility.,

As an experienced AI Architect, your role will involve leading the design, development, and deployment of large-scale AI solutions. You will be responsible for bridging the gap between business requirements and technical implementation, with a focus on generative AI and modern MLOps practices. Key Responsibilities: - Architect end-to-end AI systems utilizing large language models and generative AI technologies - Design scalable, production-ready AI applications that align with business objectives and performance requirements - Evaluate and integrate LLM APIs from leading providers such as OpenAI, Anthropic Claude, and Google Gemini - Establish best practices for prompt engineering, model selection, and AI system optimization - Fine-tune open-source models like Llama and Mistral for specific business use cases - Implement custom training pipelines and evaluation frameworks - Optimize model performance, latency, and cost for production environments - Stay updated with the latest model architectures and fine-tuning techniques - Deploy and manage AI models at an enterprise scale using containerization (Docker) and orchestration (Kubernetes) - Build robust, scalable APIs using FastAPI and similar frameworks - Design and implement MLOps pipelines for model versioning, monitoring, and continuous deployment - Ensure high availability, security, and performance of AI systems in production - Collaborate with stakeholders to understand business problems and translate them into technical requirements - Provide technical guidance and mentorship to development teams - Conduct feasibility assessments and technical due diligence for AI initiatives - Create technical documentation, architectural diagrams, and implementation roadmaps Required Qualifications: - 7+ years of experience in machine learning engineering or data science - Proven track record of delivering large-scale ML solutions Technical Skills: - Expert-level proficiency with LLM APIs (OpenAI, Claude, Gemini, etc.) - Hands-on experience fine-tuning transformer models (Llama, Mistral, etc.) - Strong proficiency in FastAPI, Docker, and Kubernetes - Experience with ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers) - Proficiency in Python and modern software development practices - Experience with cloud platforms (AWS, GCP, or Azure) and their AI/ML services Core Competencies: - Strong understanding of transformer architectures, attention mechanisms, and modern NLP techniques - Experience with MLOps tools and practices (model versioning, monitoring, CI/CD) - Ability to translate complex business requirements into technical solutions - Strong problem-solving skills and architectural thinking Preferred Qualifications: - Experience with vector databases and retrieval-augmented generation (RAG) systems - Knowledge of distributed training and model parallelization techniques - Experience with model quantization and optimization for edge deployment - Familiarity with AI safety, alignment, and responsible AI practices - Experience in specific domains (finance, healthcare, legal, etc.) - Advanced degree in Computer Science, AI/ML, or related field,

Role Overview: You are a seasoned Data Science Engineer responsible for spearheading the development of intelligent, autonomous AI systems. Your role involves designing and deploying AI solutions that leverage Retrieval-Augmented Generation (RAG), multi-agent frameworks, and hybrid search techniques to enhance enterprise applications. Key Responsibilities: - Design & Develop Agentic AI Applications: Utilise frameworks like LangChain, CrewAI, and AutoGen to build autonomous agents capable of complex task execution. - Implement RAG Pipelines: Integrate LLMs with vector databases (e.g., Milvus, FAISS) and knowledge graphs (e.g., Neo4j) to create dynamic, context-aware retrieval systems. - Fine-Tune Language Models: Customise LLMs (e.g., Gemini, chatgpt, Llama) and SLMs (e.g., Spacy, NLTK) using domain-specific data to improve performance and relevance in specialised applications. - NER Models: Train OCR and NLP leveraged models to parse domain-specific details from documents (e.g., DocAI, Azure AI DIS, AWS IDP). - Develop Knowledge Graphs: Construct and manage knowledge graphs to represent and query complex relationships within data, enhancing AI interpretability and reasoning. - Collaborate Cross-Functionally: Work with data engineers, ML researchers, and product teams to align AI solutions with business objectives and technical requirements. - Optimise AI Workflows: Employ MLOps practices to ensure scalable, maintainable, and efficient AI model deployment and monitoring. Qualifications Required: - 8+ years of professional experience in AI/ML development, with a focus on agentic AI systems. - Proficient in Python, Python API frameworks, SQL, and familiar with AI/ML frameworks such as TensorFlow or PyTorch. - Experience in deploying AI models on cloud platforms (e.g., GCP, AWS). - Experience with LLMs (e.g., GPT-4), SLMs (Spacy), and prompt engineering. Understanding of semantic technologies, ontologies, and RDF/SPARQL. - Familiarity with MLOps tools and practices for continuous integration and deployment. - Skilled in building and querying knowledge graphs using tools like Neo4j. - Hands-on experience with vector databases and embedding techniques. - Familiarity with RAG architectures and hybrid search methodologies. - Experience in developing AI solutions for specific industries such as healthcare, finance, or e-commerce. - Strong problem-solving abilities and analytical thinking. Excellent communication skills for cross-functional collaboration. Ability to work independently and manage multiple projects simultaneously.,

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Your Role Design, implement, and maintain end-to-end ML pipelines for model training, evaluation, and deployment Collaborate with data scientists and software engineers to operationalize ML models, serving frameworks (TensorFlow Serving, TorchServe) and experience with MLOps tools Develop and maintain CI/CD pipelines for ML workflows Implement monitoring and logging solutions for ML models, experience with ML model serving frameworks (TensorFlow Serving, TorchServe) Optimize ML infrastructure for performance, scalability, and cost-efficiency Your Profile Strong programming skills in Python (5+ years), with experience in ML frameworks understanding of ML-specific testing and validation techniques Expertise in containerization technologies (Docker) and orchestration platforms (Kubernetes), Knowledge of data versioning and model versioning techniques Proficiency in cloud platform (AWS) and their ML-specific services with atleast 2-3 years of experience. Strong understanding of DevOps practices and tools (GitLab, Artifactory, Gitflow etc.) Experience with monitoring and observability tools (Prometheus, Grafana, ELK stack) and knowledge of distributed training techniques What you'll love about working here We recognise the significance of flexible work arrangements to provide support in hybrid mode, you will get an environment to maintain healthy work life balance Our focus will be your career growth & professional development to support you in exploring the world of opportunities. Equip yourself with valuable certifications & training programmes in the latest technologies such as MLOps, Machine Learning Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

You should have strong programming experience in Python and hands-on expertise with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, etc. Additionally, experience with data engineering including SQL, data pipelines, ETL, APIs, and big data tools is preferred. Knowledge of MLOps tools like Docker, Kubernetes, MLflow, Airflow, and CI/CD for ML is required. Experience with cloud platforms like AWS, Azure, GCP and deploying scalable ML solutions is a plus. You should have a solid understanding of machine learning algorithms, deep learning, NLP, or computer vision depending on project needs. Strong problem-solving skills are essential, with the ability to convert business challenges into technical AI/ML solutions. For Lead/Architect roles, proven ability in team leadership, solution design, stakeholder management, and driving technical strategy is required.,

As a Data Science Engineer at the VP level in Bangalore, India, you will be responsible for leading the development of intelligent, autonomous AI systems. Your role will involve designing and deploying AI solutions that leverage technologies such as Retrieval-Augmented Generation (RAG), multi-agent frameworks, and hybrid search techniques to enhance enterprise applications. You will have the opportunity to design and develop agentic AI applications using frameworks like LangChain, CrewAI, and AutoGen to build autonomous agents capable of complex task execution. Additionally, you will implement RAG pipelines by integrating LLMs with vector databases (e.g., Milvus, FAISS) and knowledge graphs (e.g., Neo4j) to create dynamic, context-aware retrieval systems. You will also be responsible for fine-tuning language models, training NER models, developing knowledge graphs, collaborating cross-functionally, and optimizing AI workflows. To be successful in this role, you should have at least 13 years of professional experience in AI/ML development, proficiency in Python, Python API frameworks, SQL, and familiarity with frameworks such as TensorFlow or PyTorch. Experience in deploying AI models on cloud platforms (e.g., GCP, AWS) and knowledge of LLMs, SLMs, semantic technologies, ontologies, and MLOps tools and practices is essential. Additionally, you should be skilled in building and querying knowledge graphs, have hands-on experience with vector databases and embedding techniques, and be familiar with RAG architectures and hybrid search methodologies. You will receive support through training and development opportunities, coaching from experts in your team, and a culture of continuous learning to aid in your progression. The company promotes a positive, fair, and inclusive work environment, welcoming applications from all individuals. Join us at Deutsche Bank Group, where we strive for excellence together every day. For more information about our company and teams, please visit our website: https://www.db.com/company/company.htm,

Your opportunity to make a real impact and shape the future of financial services is waiting for you. Let's push the boundaries of what's possible together As an Applied AI/GenAI ML Director within the Asset and Wealth Management Technology Team at JPMorgan Chase, you will provide deep engineering expertise and work across agile teams to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. You will leverage your deep expertise to consistently challenge the status quo, innovate for business impact, lead the strategic development behind new and existing products and technology portfolios, and remain at the forefront of industry trends, best practices, and technological advances. This role will focus on establishing and nurturing common capabilities, best practices, and reusable frameworks, creating a foundation for AI excellence that accelerates innovation and consistency across business functions Job Responsibilities: Lead the development and implementation of GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes. Oversee the design, deployment, and management of prompt-based models on LLMs for various NLP tasks in the financial services domain. Conduct and guide research on prompt engineering techniques to improve the performance of prompt-based models within the financial services field, exploring and utilizing LLM orchestration and agentic AI libraries. Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization. Communicate effectively with both technical and non-technical stakeholders, including senior leadership. Build and maintain data pipelines and data processing workflows for prompt engineering on LLMs utilizing cloud services for scalability and efficiency. Develop and maintain tools and frameworks for prompt-based model training, evaluation, and optimization. Analyze and interpret data to evaluate model performance and identify areas of improvement. Required qualifications, capabilities, and skills: Formal training or certification on Machine Learning concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise. Hands-on experience in building Agentic AI solutions. Familiarity with LLM orchestration and agentic AI libraries. Strong programming skills in Python with experience in PyTorch or TensorFlow. Experience building data pipelines for both structured and unstructured data processing. Experience in developing APIs and integrating NLP or LLM models into software applications. Hands-on experience with cloud platforms (AWS or Azure) for AI/ML deployment and data processing. Excellent problem-solving skills and the ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner. Basic knowledge of deployment processes, including experience with GIT and version control systems. Hands-on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environments. Preferred Qualifications, Capabilities, and Skills: Familiarity with model fine-tuning techniques. Knowledge of financial products and services, including trading, investment, and risk management.

As a Senior Software Engineer with AI Platform, you will play a crucial role in the team tasked with designing and developing the next generation of scalable Kubernetes infrastructure intertwined with machine learning platforms. These platforms will support both traditional ML and innovative Large Language Models (LLMs). If you have experience in engineering, this position offers you the opportunity to lead the technical direction, ensuring the performance, reliability, and scalability of AI systems. You will collaborate closely with data scientists, researchers, and other engineering teams to achieve these goals. You will be expected to define the architecture for our Kubernetes platform, mentor a team of junior software engineers, and enhance expertise in AI/ML. Your responsibilities will involve designing and developing advanced ML pipelines, constructing scalable infrastructure, and implementing Infrastructure as Code standard methodologies using Golang. Furthermore, you will work alongside AI and MLOps frameworks to shape the adoption of modern technologies and processes. Your leadership will not only foster a culture of innovation but also strengthen the team's technical foundation through mentorship. This role is ideal for individuals passionate about tackling sophisticated engineering challenges within the dynamic AI/ML space and delivering impactful, scalable solutions. Your primary responsibilities as a Software Engineer with AI/ML Platform Experience will include architecting and designing scalable Kubernetes platforms supporting both traditional ML and Large Language Models (LLMs). You will also provide client support for hosting AI/ML workload on Kubernetes platforms, and lead the development of end-to-end ML pipelines. Additionally, you will drive AIOPs initiatives across the Middleware platform by collaborating with multifunctional teams to operationalize and optimize ML models effectively. Your role will also involve defining and implementing MLOps standard methodologies and developing infrastructure automation tools to improve efficiency across teams. Ensuring platform reliability, scalability, and performance through meticulous engineering practices will be crucial, along with conducting code reviews, establishing standard processes, and mentoring junior engineers. Lastly, staying updated on the latest trends in AI/ML to influence platform enhancements will be essential. Minimum Qualifications: - 10+ years of software engineering experience, including at least 2+ years in AI & machine learning-related roles. - Expertise in Golang or Python, with hands-on experience with Kubernetes platform and ML frameworks (TensorFlow, PyTorch). - Subject matter expertise with microservice architecture, SSO, and containerized cloud applications. - Consistent track record in designing and deploying scalable machine learning systems in production. - Deep understanding of ML algorithms, data pipelines, and optimization techniques. - Experience building CI/CD pipelines for ML workflows, including model monitoring and retraining. - Proficiency in cloud platforms and orchestration tools for distributed systems. - Strong problem-solving and debugging skills for complex, large-scale systems. - Experience in mentoring engineers and driving technical decision-making. Preferred Qualifications: - Expert understanding in Kubernetes for managing production-grade systems and ensuring scalability. - Expertise in Golang or Python. - Strong hand-on with architecting and optimizing workflows using Kubeflow pipelines, KServe, Airflow, and MLflow. - Experience of LangChain and experience designing RAG systems. - Consistent track record of designing and leading the development of distributed systems. - Experience with implementing robust inter-service communication patterns and solving scalability issues. #WeAreCisco where every individual brings their unique skills and perspectives together to pursue our purpose of powering an inclusive future for all. Cisco values connection, celebrates diversity, and focuses on unlocking potential. Cisconians experience one company with many careers, where learning and development are encouraged at every stage. Cisco's technology, tools, and culture pioneer hybrid work trends, enabling all employees to give their best. Cisco understands the opportunity to bring communities together and believes that its people are at the heart of that mission. Cisco's purpose, driven by its people, makes it the worldwide leader in technology that powers the internet. Cisco ensures that every step taken is a step towards a more inclusive future for all. Join Cisco and take your next step towards being yourself with them!,

As an experienced Machine Learning Engineer with over 6 years of total experience, including more than 5 years in relevant Machine Learning roles, you will be responsible for building and scaling mission-critical ML systems to optimize core capabilities. Your primary focus will be on designing and deploying end-to-end ML pipelines, encompassing the entire process from training to monitoring. Utilizing supervised, unsupervised, and deep learning methods, you will tackle various business challenges by implementing scalable solutions using tools such as TensorFlow, PyTorch, and Scikit-learn. In this role, you will play a key part in driving MLOps adoption within the organization, leveraging tools like MLflow and Kubeflow to enhance operational efficiency. Collaboration with engineering and data science teams is essential to ensure the successful delivery of production-grade ML solutions. Additionally, you will have the opportunity to mentor junior engineers, guiding them towards best practices in the field. A keen eye for emerging ML trends and the ability to implement them effectively are crucial aspects of this position. Your technical skills should include proven expertise in ML algorithms, deep learning frameworks, and statistical modeling. Proficiency in Python is a must, along with hands-on experience in TensorFlow, PyTorch, and Scikit-learn. Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, and CI/CD, is required. Exposure to cloud platforms like AWS, Azure, and GCP will be beneficial. While a background in energy/utilities is considered a plus, it is not mandatory for this role. If you are passionate about leveraging Machine Learning to solve complex problems and eager to contribute to a dynamic team, we encourage immediate joiners to apply. This is a 12-month contract position based in Pune, with the possibility of extension based on performance. Background verification is mandatory for all applicants.,

At Yuja, a highly scalable and modular platform for on-demand shared mobility and last-mile connectivity is being developed. The development process involves various dimensions, providing a unique opportunity to work on deep tech solutions. The tech stack includes IoT devices for smart shared services, ML and data workflows, user experiences, and a focus on accessibility. Original thinking, experimentation, and measurable product development are emphasized. As a role at Yuja, you will be responsible for understanding product use cases and developing workflows for ML-driven features. This includes developing and maintaining dynamic ML models, ML-oriented testing procedures, algorithm research, and development. You will plan data collection programs, conduct model testing, and system feature testing. Additionally, deploying real-time algorithms, heuristics, and ML models, integrating ML workflows with other system components, and building reusable code are part of the role. Participation in DevOps and MLOps workflows, as well as managing internal or external resources, is required. The applications of ML/AI at Yuja span multiple domains such as time-series problems, agent-based modeling, image processing, contextual text generation, and recommendation. Highlighting your core experience in ML/AI in your application submission or resume is essential. Basic qualifications include a B.E./B.Tech. in Computer Science or related fields with experience in machine learning, image and signal processing, or statistics. Strong knowledge of probability theory, statistics, calculus, vector algebra, and ML algorithms is required. Proficiency in Python, data structures, algorithms, and ML pipeline is necessary. Experience with AWS/GCP ML stack, industry-standard ML frameworks, databases, and excellent communication skills are also key requirements. Preferred qualifications include exposure to GIS, graph theory, agent-based modeling, optimization theory, MLOps tools, spatial data analysis, containerization, and data visualization. The job type is full-time and permanent with a requirement to commute/relocate to Ahmedabad, Gujarat. Applicants should have 2+ years of experience, with education at the Bachelor's level. The application deadline is 07/03/2025, and the expected start date is 17/03/2025.,

We are seeking a highly motivated AI Engineer with a solid background in artificial intelligence and practical experience in developing AI-driven products. As an AI Engineer, you will play a key role in the design, development, and deployment of AI models and solutions that enhance our range of products and services. This position is particularly well-suited for recent graduates who have gained hands-on experience through internships, academic projects, or previous roles in the AI field. Your responsibilities will include designing, optimizing, and implementing machine learning (ML) and deep learning (DL) models to enhance AI-powered applications. You will collaborate closely with data scientists and software engineers to gather, preprocess, and analyze large datasets for AI training and inference. Additionally, you will be involved in fine-tuning AI algorithms for various tasks such as natural language processing (NLP), computer vision, recommendation systems, and predictive analytics. Ensuring the scalability, efficiency, and reliability of AI models in production environments will be a critical aspect of your role. You will work collaboratively with cross-functional teams to seamlessly integrate AI solutions into our products and business processes. Staying abreast of the latest advancements in AI, ML, and deep learning will be essential, and you will be expected to write clean, efficient, and well-documented code using Python, LangChain, or other AI frameworks. Your involvement in model evaluation and consultation with other teams to assist the CEO of the unit will be pivotal in driving the success of our AI initiatives. Requirements: - Bachelor's or Master's degree in Artificial Intelligence, Data Science, or equivalent experience of at least 5 years. - Proficiency in Python and familiarity with SQL and JavaScript. - Experience with Agentic AI. - Knowledge of cloud platforms such as AWS, Azure, Google Cloud, and MLOps tools. - Understanding of data structures, algorithms, and software engineering principles, including prototyping. - Hands-on experience with data preprocessing, feature engineering, and model evaluation techniques. - Strong problem-solving skills and the ability to thrive in a fast-paced, collaborative environment. - Excellent communication skills to effectively convey technical concepts to non-technical stakeholders. - Familiarity with LLMs and tools like openAI, Deepseek for AI applications. - Experience in building presentations and consulting. Preferred Qualifications: - Practical experience with real-world AI applications, whether through internships, research, or personal projects. - Familiarity with version control systems (Git), CI/CD pipelines, and containerization (Docker, Kubernetes). What We Offer: - Competitive Salary and Bonus to acknowledge your expertise and contributions. - Hybrid work environment allowing for a mix of remote work and in-office collaboration. - Inclusive Onboarding Experience tailored to set you up for success from day one. - Marcura Wellness Zone to support your work-life balance and overall well-being. - Global Opportunities within our ambitious and expanding company. - Monthly Performance Support through our modern performance management framework. - Diverse, Supportive Work Culture committed to inclusion, diversity, and belonging for all team members. If you are passionate about AI and excited to apply your skills to real-world maritime challenges, we encourage you to apply and join our innovative AI team. Your expertise and dedication will play a crucial role in shaping the future of our AI-driven products and services.,

The project involves the development of an AI-based door control system that utilizes computer vision and deep learning technologies to manage boardings and exits through real-time video analysis. This system aims to detect individuals and objects in doorways, replacing traditional sensors with a single AI-powered solution. The project includes the implementation of deep learning models for people and object recognition, movement analysis, real-time processing, decision-making, and logging. The system must process video data on the edge, requiring models optimized for embedded deployment while ensuring detection accuracy and speed. It should function reliably under varying lighting conditions and handle complex scenarios such as multiple passengers, carried objects, and potential obstructions while adhering to strict safety standards. Task Descriptions: Task 1: Data Analysis and Annotation - Categorize data for analysis - Annotate data for training and validation purposes Task 2: Model Evaluation and Performance Analysis - Conduct comprehensive testing to generate detailed daily performance reports - Analyze and document detection failures and performance issues - Develop recommendations for model improvements based on observed failure patterns Task 3: Model Enhancement and Optimization - Prepare data for model training - Develop and optimize deep learning models Task 4: Extended Vision Capabilities - Enhance the system's vision capabilities for improved performance Required Skillset: - Strong expertise in computer vision and deep learning, particularly with PyTorch / TensorFlow and object detection models - Experience in data annotation, preparation, and validation for computer vision applications - Proficiency in model optimization, testing, and deployment on edge devices - Familiarity with MLOps tools such as AWS Sage Maker, DVC, and version control systems Input: - Existing labeled dataset from current deployments - New video data from existing installations - Current model architecture and weights - System performance requirements and specifications,

You are seeking an AI Architect to lead the design, development, and deployment of advanced AI systems, with a strong emphasis on Large Language Models (LLMs), fine-tuning, and customer experience (CX) technologies. This role blends deep technical expertise with leadership, research, and infrastructure planning to deliver intelligent, scalable, and customer-centric AI solutions across cloud and on-premise environments. Key Responsibilities LLM Development & Fine-Tuning - Architect and implement scalable solutions for training and fine-tuning LLMs. - Apply prompt engineering, transfer learning, and optimization techniques to enhance model performance. - Integrate LLMs into customer-facing applications such as chatbots, VOICE AI agents, Expert AI agents, and recommendation engines. Customer Experience (CX) Technology Integration - Collaborate with CX and product teams to embed AI into customer journeys, improving personalization, automation, and engagement. - Design AI-driven solutions for omnichannel support, sentiment analysis, and real-time feedback loops. - Ensure AI systems align with customer satisfaction goals and ethical AI principles. Technical Leadership & Team Management - Lead and mentor a multidisciplinary team of AI engineers, data scientists, and MLOps professionals. - Drive agile development practices and foster a culture of innovation and accountability. Research & Innovation - Conduct and apply research in NLP, LLMs, and AI infrastructure to solve real-world customer experience problems. - Contribute to publications, patents, or open-source initiatives as appropriate. - Guide team and maintain detailed architecture diagrams, design documents, and technical specifications. Product Roadmap & Delivery - Define and execute the AI product roadmap in collaboration with engineering and business stakeholders. - Manage timelines, deliverables, and cross-functional dependencies. - Plan and manage GPU infrastructure for training and inference (e.g., A100, H100, L40S). Deployment & MLOps - Deploy AI models on Azure, AWS, and on-premise GPU clusters using containerized and scalable architectures. - Integrate with CI/CD pipelines and ensure robust monitoring, logging, and rollback mechanisms. Qualifications - Masters or Ph.D. in Computer Science, AI, Machine Learning, or related field. - 5+ years of experience in AI/ML, with 1.5 + years in a leadership or GEN AI architect role. - Proven experience with LLMs, Transformers, and fine-tuning frameworks (e.g., Hugging Face). - Strong understanding of customer experience platforms and how AI can enhance them. - Proficiency in Python, PyTorch, TensorFlow, and MLOps tools. - Experience with cloud platforms (Azure, AWS) and on-premise GPU infrastructure. Why Join Us - Shape the future of AI-powered customer experiences, visibility to global customer AI deployments. - Lead a high-impact team working on state-of-the-art technologies. - Competitive compensation, and continuous learning opportunities.,

The ideal candidate for this position should possess a Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field, or have equivalent practical experience. You should have a proven track record of hands-on experience in Machine Learning/Artificial Intelligence, including deploying, fine-tuning, or integrating large-scale Natural Language Processing (NLP) models or other advanced ML solutions. Proficiency in Python (specifically PyTorch or TensorFlow) and familiarity with MLOps tools such as Airflow, MLflow, and Docker is required. An understanding of data privacy frameworks, encryption, and secure data handling practices is crucial, particularly for handling sensitive internal documents. Additionally, you should be comfortable with setting up continuous integration/continuous delivery (CI/CD) pipelines, container orchestration (Kubernetes), and version control (Git). Strong communication skills and experience working collaboratively with both technical and non-technical teams are essential for this role. As a part of your role, you will collaborate with cross-functional teams to develop AI-driven applications aimed at enhancing productivity and reporting. You will lead integrations with hosted AI solutions like ChatGPT, Claude, and Grok, ensuring immediate functionality without compromising sensitive data while laying the groundwork for a robust in-house AI infrastructure. Your responsibilities will also include developing and maintaining on-premises large language model (LLM) solutions like Llama to safeguard data privacy and intellectual property. Key Responsibilities: - Own the LLM pipeline by setting up, fine-tuning, and deploying on-prem LLMs, managing data ingestion, cleaning, and maintenance for domain-specific knowledge bases. - Assist the IT department in implementing role-based access controls, encryption protocols, and best practices for protecting sensitive engineering data. - Oversee hardware/server configurations (or cloud alternatives) for AI workloads, evaluating resource usage and optimizing model performance. - Develop and maintain internal AI-driven applications and services, such as automated report generation, advanced analytics, RAG interfaces, and custom desktop applications. - Collaborate with project managers and domain experts to automate routine deliverables and speed up existing workflows. - Define coding standards, maintain technical documentation, and promote CI/CD and DevOps practices for AI software. - Provide guidance to data analysts and junior developers on AI tool usage, ensuring alignment with internal policies and minimizing model hallucinations. - Monitor AI system metrics (speed, accuracy, utilization) and implement updates or retraining as needed. This is a full-time permanent position with benefits including health insurance, provident fund, yearly bonus, day shifts from Monday to Friday, and an in-person work location. The application deadline is 30/06/2025, with an expected start date of 10/06/2025.,

As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. The AI/ML Platform Engineering Lead is a pivotal leadership role responsible for managing the day-to-day operations and development of the AI/ML platform team. In this role, you will guide the team in designing, building, and maintaining scalable platforms, while collaborating with other engineering and data science teams to ensure successful model deployment and lifecycle management. Key Responsibilities: - Lead and manage a team of platform engineers in developing and maintaining robust AI/ML platforms - Define and implement best practices for machine learning infrastructure, ensuring scalability, performance, and security - Collaborate closely with data scientists and DevOps teams to optimize the ML lifecycle from model training to deployment - Establish and enforce standards for platform automation, monitoring, and operational efficiency - Serve as the primary liaison between engineering teams, product teams, and leadership - Mentor and develop junior engineers, providing technical guidance and performance feedback - Stay abreast of the latest advancements in AI/ML infrastructure and integrate new technologies where applicable Qualifications: - Bachelors or Masters degree in Computer Science, Engineering, or a related field - 8+ years of experience in AI/ML platform development and infrastructure - Proven experience in leading engineering teams and driving large-scale projects - Extensive expertise in cloud infrastructure (AWS, GCP, Azure), MLOps tools (e.g., Kubeflow, MLflow), and infrastructure as code (Terraform) - Strong programming skills in Python and Node.js, with a proven track record of building scalable and maintainable systems that support AI/ML workflows - Hands-on experience with monitoring and observability tools, such as Datadog, to ensure platform reliability and performance - Strong leadership and communication skills with the ability to influence cross-functional teams - Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment,

As an AI Architect at Datafoundry AI, a leading AI-first company driving digital transformation, you will be a key player in shaping cutting-edge AI solutions for various industries. With a primary focus on the Life Sciences sector, especially in the Safety Vigilance domain, Datafoundry is at the forefront of developing AI/ML algorithms to address digitalization challenges across sectors like Healthcare, Utilities, Aerospace and Defence, Manufacturing, and Banking. In this role, you will be responsible for conceptualizing and architecting AI solutions that meet evolving requirements and drive innovation in computer vision, Natural Language Processing (NLP), and reinforcement learning domains. Your leadership will be crucial in ensuring the scalability, performance, availability, and real-world impact of intelligent systems. Particularly, your expertise will be instrumental in healthcare and clinical data environments, making prior exposure to these domains highly desirable. Your key responsibilities will include leading the design, development, and scaling of AI platforms and products, defining non-functional requirements like scalability and reliability, documenting system architectures using industry-standard practices, and fostering technical growth within the engineering team. Your technical skills and expertise should span computer vision, NLP, Explainable AI (XAI) methods, Reinforcement Learning (RL), data lake development, data fabric architectures, and ML pipeline engineering in hybrid environments. If you are a visionary AI/ML Architect with over 10 years of experience, and a passion for driving AI innovation in a collaborative environment, Datafoundry invites you to join our team. You will be part of an exciting journey that transforms how organizations harness data for a competitive advantage. Apart from an attractive compensation package, we offer a flexible remote work environment and ample opportunities for professional development. If you are ready to be at the forefront of AI transformation and contribute to groundbreaking solutions across diverse industry sectors, apply now to be a part of Datafoundry's dynamic team.,

As a Senior AI Engineer at our company, you will be responsible for leading the design, development, and deployment of cutting-edge AI and machine learning models. We are looking for a highly skilled and motivated individual with a strong background in algorithms, deep learning, data engineering, and software development. Your passion for solving real-world problems through AI will be instrumental in this role. Your key responsibilities will include designing and developing scalable AI and machine learning models to solve complex business challenges. You will lead end-to-end model development, from data collection and preprocessing to training, validation, deployment, and monitoring. Collaboration with cross-functional teams, including data engineers, software developers, and product managers, will be essential. Additionally, you will be optimizing existing AI models for performance and accuracy, staying updated with the latest research and trends in AI/ML, and documenting processes, models, and code to ensure knowledge sharing and reproducibility. Mentoring junior team members and contributing to a culture of innovation and excellence will also be part of your role. To be successful in this position, you should have a Bachelors or Masters degree in Computer Science, Data Science, Engineering, or a related field, along with at least 5 years of experience in AI/ML, data science, or related roles. Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, and scikit-learn is required. A solid understanding of machine learning algorithms, data structures, and software engineering principles is also essential. Experience with cloud platforms like AWS, Azure, or GCP, as well as MLOps tools, will be beneficial. Hands-on experience with NLP, computer vision, or deep learning applications, strong problem-solving and analytical skills, and excellent communication and collaboration abilities are desired qualities. Preferred qualifications for this role include a PhD in an AI/ML-related field, experience deploying models in production environments using CI/CD pipelines, and contributions to open-source AI/ML projects or publications in top-tier journals/conferences. In return, we offer a competitive salary, performance bonuses, career growth opportunities, and the chance to work with a passionate and innovative team on impactful projects. This is a full-time, permanent position with a Monday to Friday work schedule. The work location is in person.,

As an Artificial Intelligence Developer/AI Developer at APPWRK IT Solutions Pvt. Ltd., you will be part of a team dedicated to delivering high-quality solutions tailored to our clients" needs. Located in Mohali, our company has a strong global presence and is well-known for collaborating with Fortune 500 clients like Unilever. You will play a key role in developing, training, validating, and deploying AI/ML models for real-world use cases. Collaborating with cross-functional teams, you will define and implement end-to-end AI systems. Additionally, you will design and maintain scalable APIs and microservices, as well as build user-friendly front-end interfaces to support AI-powered applications. It is essential to write clean, maintainable, and testable code for both client-side and server-side components. As part of your responsibilities, you will implement MLOps practices, conduct performance tuning, A/B testing, and continuously evaluate models for improvement. Staying updated with the latest technologies and best practices in AI and software engineering is crucial for this role. The ideal candidate should possess a Bachelor's/Master's degree in Computer Science, Artificial Intelligence, or related fields, with at least 1-5 years of experience in AI/ML development using Python, TensorFlow, PyTorch, or similar technologies. Strong understanding of data structures, algorithms, machine learning concepts, and model evaluation is required. Proficiency in backend frameworks like Django, Flask, or FastAPI, along with solid front-end development skills using React, Angular, or Vue.js is preferred. Experience with RESTful APIs, GraphQL, containerization (Docker/Kubernetes), cloud platforms (AWS, GCP, Azure), databases (SQL and NoSQL), and version control (Git) is necessary. Knowledge of AI deployment pipelines, model serving, and monitoring tools is also essential. Preferred skills include experience with LLMs, knowledge of data annotation tools, NLP, Computer Vision, exposure to CI/CD pipelines, MLOps tools, and contributions to open-source projects or AI hackathons. Soft skills such as problem-solving, analytical abilities, communication, collaboration, and the ability to deliver in a fast-paced environment are highly valued. If you are a motivated developer with a passion for AI and looking for a rewarding opportunity, apply now to join our growing team at APPWRK IT Solutions Pvt. Ltd. This is a full-time position with benefits including health insurance and provident fund. The work schedule is day shift, Monday to Friday, and the job requires in-person work in Mohali, Punjab. Application Question: How many years of work experience do you have in AI/ML Development ,

We are looking for a ML Engineer /Senior ML Engineer with hands-on experience in Generative AI (GenAI) to drive innovation through cutting-edge AI/ML solutions. This role involves designing and implementing GenAI models and pipelines that solve business problems and enhance productivity. You will collaborate with cross-functional teams to deliver solutions using large language models (LLMs), transformers, and other generative techniques. Key Responsibilities: Develop and fine-tune Generative AI models using LLMs (e.g., GPT, LLaMA, Claude, PaLM) for tasks like summarization, content generation,question answering, semantic search, etc. Build end-to-end GenAI-powered solutions including prompt engineering, model training/fine-tuning, evaluation, and deployment. Use frameworks like LangChain, LlamaIndex, and vector databases (e.g.,FAISS, Pinecone, Weaviate) to build RAG (Retrieval-Augmented Generation) pipelines. Collaborate with product, engineering, and business stakeholders to identify AI opportunities and prototype solutions. Conduct experiments, evaluate model performance, and optimize for accuracy, latency, and relevance. Contribute to the development of GenAI best practices and reusable assets within the organization. Stay up to date with the latest research and developments in the GenAI and LLM space. Required Skills and Experience: 2+ years of experience in ML/AI roles, with 2+ focus on GenAI or LLMs. Strong Python skills and experience with transformers, Hugging Face, PyTorch, or TensorFlow. Deep understanding of NLP, language modeling, and generative techniques. Experience with prompt engineering, fine-tuning or few-shot learning. Hands-on experience with LangChain, LlamaIndex, vllm or similar GenAI orchestration frameworks. Working knowledge of vector stores, embedding models, and retrieval techniques. Experience with model deployment in cloud or hybrid environments (e.g., Azure, AWS, GCP). Familiarity with MLOps tools and best practices is a plus.

We are looking for a passionate and skilled Generative AI Specialist with expertise in state-of-the-art AI models and tools to become a valuable member of our team. The ideal candidate should have hands-on experience with transformer-based models, prompt engineering, and fine-tuning large language models (LLMs) for practical applications. As a Generative AI Specialist, your responsibilities will include designing, developing, and implementing Generative AI solutions using models such as GPT, Llama, Claude, and other open-source resources. You will be expected to fine-tune and optimize pre-trained models on specific datasets, build and evaluate prompts, and create retrieval-augmented generation (RAG) pipelines for various LLM applications. Additionally, you will work on developing multimodal models that combine text, image, and/or audio data based on project requirements, collaborating with product, data science, and engineering teams to integrate AI capabilities into our products. It is important to stay updated with the latest developments in generative AI and apply them to solve business problems effectively. Furthermore, you will be responsible for maintaining model performance through testing, benchmarking, and continuous improvements. Key Skills Requirements: - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field - Demonstrated expertise in on-premises infrastructure and technologies - 1-3 years of practical experience with Natural Language Processing (NLP) or generative AI models - Proficiency in Python and machine learning frameworks like PyTorch or TensorFlow - Hands-on experience with tools such as Hugging Face Transformers, LangChain, or LlamaIndex - Deep understanding of model fine-tuning, embeddings, and vector databases (e.g., FAISS, Pinecone) - Familiarity with cloud platforms like AWS, Google Cloud Platform (GCP), or Microsoft Azure - Strong analytical and problem-solving skills with a collaborative mindset for fast-paced environments - Experience in diffusion models, image/video generation, or speech synthesis - Knowledge of MLOps tools and end-to-end model deployment pipelines - Contributions to open-source AI/ML projects are highly valued Join us at Beinex and enjoy a range of perks including comprehensive health plans, learning and development opportunities, workation and outdoor training, a hybrid working environment, and on-site travel opportunities. Be part of a dynamic team that values innovation and growth.,

We are looking for an accomplished and hands-on Senior AI Lead to drive the development and deployment of AI-powered solutions for supply chain optimization. This senior technical leadership role requires deep AI/ML expertise, client-facing engagement, and team management to deliver intelligent, scalable products on the AWS cloud platform. You will be responsible for leading the end-to-end lifecycle of AI solutions that address real-world supply chain challenges such as demand planning and forecasting, inventory optimization, purchasing, fulfillment, route planning, risk prediction, and anomaly detection. Your key responsibilities will include designing, building, and deploying AI/ML models tailored for supply chain use cases, implementing scalable, cloud-native ML pipelines using AWS services, collaborating with domain experts to translate supply chain data into actionable AI models and insights, interfacing directly with supply chain and logistics clients to understand pain points, communicating technical concepts to business stakeholders, guiding clients on the adoption and integration of AI technologies, leading workshops, discovery sessions, and project scoping discussions, analyzing the AI/ML landscape in the context of supply chain challenges and emerging AWS capabilities, defining and owning the AI technical roadmap and architectural vision, conducting architecture reviews, ensuring scalability, and setting best practices across the AI engineering lifecycle, leading model deployment and operationalization efforts in real-world supply chain environments, ensuring reliability, observability, and resilience of deployed AI models, working closely with DevOps and infrastructure teams for CI/CD, cost optimization, and security compliance, managing and mentoring a team of AI/ML engineers and data scientists, promoting a collaborative, growth-oriented engineering culture, leading hiring, onboarding, and performance management for the AI team. The required qualifications for this role include a Bachelors or Masters degree in Computer Science, Engineering, Data Science, or a related field, 10+ years of experience in software/data engineering with a focus on AI/ML development, 3+ years in a leadership role managing AI/ML teams or projects, strong expertise in Python and ML frameworks, proven experience building and deploying AI/ML solutions on AWS, strong client communication, problem-solving, and strategic thinking skills. Preferred qualifications include experience with MLOps tools and data pipelines, exposure to advanced AI use cases, AWS Certified Machine Learning Specialty or equivalent credentials, domain experience in supply chain, logistics, or manufacturing. Join us to lead transformative AI projects in a high-impact business domain, work with a forward-thinking team solving complex supply chain problems, access modern cloud-native tools, a data-rich environment, and competitive compensation, benefits, and professional growth opportunities. To apply, send your resume and a cover letter highlighting your AI and supply chain experience to careers@openlynks.ai.,

As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. The Backend Engineering Lead is a pivotal leadership role responsible for managing the day-to-day operations and development of the AI/ML platform team. In this role, you will guide the team in designing, building, and maintaining scalable platforms, while collaborating with other engineering and data science teams to ensure successful model deployment and lifecycle management. Lead and manage a team of platform engineers in developing and maintaining robust AI/ML platforms. Define and implement best practices for machine learning infrastructure, ensuring scalability, performance, and security. Collaborate closely with data scientists and DevOps teams to optimize the ML lifecycle from model training to deployment. Establish and enforce standards for platform automation, monitoring, and operational efficiency. Serve as the primary liaison between engineering teams, product teams, and leadership. Mentor and develop junior engineers, providing technical guidance and performance feedback. Stay abreast of the latest advancements in AI/ML infrastructure and integrate new technologies where applicable. Qualifications: - Bachelors or Masters degree in Computer Science, Engineering, or a related field. - 8+ years of experience in Python & Node.js development and infrastructure. - Proven experience in leading engineering teams and driving large-scale projects. - Extensive expertise in cloud infrastructure (AWS, GCP, Azure), MLOps tools (e.g., Kubeflow, MLflow), and infrastructure as code (Terraform). - Strong programming skills in Python and Node.js, with a proven track record of building scalable and maintainable systems that support AI/ML workflows. - Hands-on experience with monitoring and observability tools, such as Datadog, to ensure platform reliability and performance. - Strong leadership and communication skills with the ability to influence cross-functional teams. - Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.,

Join us at Barclays in the role of Strategic Adoption AI Engineer, where you will be tasked with enhancing existing processes, reporting, and controls to ensure flawless execution of BAU. Your responsibilities will include driving efficiencies, implementing process improvements, and standardizing processes across SBUs wherever feasible. At Barclays, we not only anticipate the future but also actively participate in creating it. To excel in this role, you should possess the following skills: - Proficient programming abilities in Python and hands-on experience with ML libraries such as scikit-learn, TensorFlow, and PyTorch. - Familiarity with automation tools like Jenkins, GitHub Actions, or GitLab CI/CD for streamlining ML pipelines. - Strong knowledge of Docker and Kubernetes for facilitating scalable deployments. - Extensive experience with various AWS services like SageMaker, Bedrock, Lambda, CloudFormation, Step Functions, S3, and IAM. - Managing infrastructure for training and inference using AWS S3, EC2, EKS, and Step Functions. - Expertise in Infrastructure as Code tools like Terraform, AWS CDK. - Familiarity with model lifecycle management tools such as MLflow, SageMaker Model Registry. - Solid understanding of applying DevOps principles to ML workflows. Additionally, valuable skills may include: - Experience with Snowflake and Databricks for collaborative ML development and scalable data processing. - Knowledge of data engineering tools like Apache Airflow, Kafka, Spark. - Understanding of model interpretability, responsible AI, and governance. - Contributions to open-source MLOps tools or communities. - Strong leadership, communication, and cross-functional collaboration skills. - Understanding of data privacy, model governance, and regulatory compliance in AI systems. - Exposure to LangChain, Vector DBs like FAISS, Pinecone, and retrieval-augmented generation (RAG) pipelines. Your assessment may focus on critical skills essential for success in this role, including risk and controls, change and transformation, business acumen, strategic thinking, and digital and technology expertise. This position is located at our Pune office. **Purpose of the role:** To design, develop, and enhance software solutions using various engineering methodologies to provide business, platform, and technology capabilities for our customers and colleagues. **Accountabilities:** - Develop and deliver high-quality software solutions using industry-aligned programming languages, frameworks, and tools. Ensure scalability, maintainability, and performance optimization of the code. - Collaborate with product managers, designers, and engineers to define software requirements, devise solution strategies, and integrate them seamlessly with business objectives. - Engage in peer collaboration, participate in code reviews, and promote a culture of code quality and knowledge sharing. - Stay updated on industry technology trends, contribute to organizational technology communities, and foster technical excellence and growth. - Adhere to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions. - Implement effective unit testing practices to ensure proper code design, readability, and reliability. **Assistant Vice President Expectations:** - Provide advice and influence decision-making, contribute to policy development, and take responsibility for operational effectiveness. Collaborate closely with other functions/business divisions. - Lead a team in performing complex tasks, using professional knowledge and skills to impact the entire business function. Set objectives, coach employees, appraise performance, and determine reward outcomes. - Demonstrate clear leadership behaviours to create an environment for colleagues to thrive and deliver excellent results. The four LEAD behaviours are: Listen and be authentic, Energise and inspire, Align across the enterprise, Develop others.,