515 Mlops Jobs - Page 5

Urgent Hiring Genpact (on role) for MLOps Engineer Permanent role Location: Hyderabad Shift Timing: 12 PM to 10 PM IST Looking for candidates with Immediate to serving notice period of 30-45 days maximum. Candidates with the right combination of ML lifecycle management , cloud infrastructure , and generative AI expertise. Breakdown: Role keywords : MLOps, LLM Ops, ML Engineer Technical skills: T echnical skills Cloud platforms : AWS, Azure Automation skills : CI/CD Containerization : Docker, Kubernetes Monitoring tools : Prometheus, Grafana With a startup spirit and 115,000+ curious and courageous minds, we have the expertise to go deep with the worlds biggest brandsand we have fun doing it. We dream in digital, dare in reality, and reinvent the ways companies work to make an impact far bigger than just our bottom line. Were harnessing the power of technology and humanity to create meaningful transformation that moves us forward in our pursuit of a world that works better for people. Now, we’re calling upon the thinkers and doers, those with a natural curiosity and a hunger to keep learning, keep growing., People who thrive on fearlessly experimenting, seizing opportunities, and pushing boundaries to turn our vision into reality. And as you help us create a better world, we will help you build your own intellectual firepower. Welcome to the relentless pursuit of better. Inviting applications for the role of Lead Consultant, ML Ops Engineer ! We are seeking a highly skilled and experienced ML Ops / LLM Ops Engineer to join our team. You will play a crucial role in building and maintaining the infrastructure and pipelines for our cutting-edge Generative AI applications, working closely with the Generative AI Full Stack Architect. Your expertise in automating and streamlining the ML lifecycle will be instrumental in ensuring the efficiency, scalability, and reliability of our Generative AI models in production. Responsibilities Design, develop, and implement ML/LLM pipelines for generative AI models, encompassing data ingestion, pre-processing, training, deployment, and monitoring. Conduct research and experimentation to explore new generative AI techniques and stay up to date with industry trends. Integrate GenAI APIs and microservices into existing applications and systems. Develop solutions leveraging GanAI technologies, integrating advanced AI capabilities into cloud native architectures to enhance system functionality and scalability. Automate ML tasks across the model lifecycle, leveraging tools like GitOps, CI/CD pipelines, and containerization technologies (e.g., Docker, Kubernetes). MLOps Support and Maintenance on ML Platforms Dataiku/Sagemaker. Implement version control, CI/CD pipelines, and containerization techniques to streamline ML and LLM workflows. Design and implement monitoring and alerting systems to track model performance, data drift, and other key metrics. Conduct ground truth analysis to evaluate the accuracy and effectiveness of LLM outputs compared to known, correct data. Work closely with infrastructure and DevOps teams to provision and manage resources for ML and LLM development and deployment. Develop and maintain robust monitoring and alerting systems for generative AI models in production, ensuring proactive identification and resolution of issues. Collaborate with the Generative AI Full Stack Architect and other engineers to optimize model performance and resource utilization. Manage and maintain cloud infrastructure (e.g., AWS, Azure) for ML workloads, ensuring cost-efficiency and scalability. Stay up to date on the latest advancements in MLOps and incorporate them into our platform and processes. Communicate effectively with technical and non-technical stakeholders about the health and performance of generative AI models. Qualifications we seek in you! Minimum Qualifications Bachelor’s degree in computer science, Data Science, Engineering, or a related field, or equivalent experience. Deep understanding of generative AI concepts, including neural networks, recurrent neural networks, and GANs. Experience in MLOps or related areas, such as DevOps, data engineering, or ML infrastructure. Proven experience in ML Ops, LLM Ops, or related roles, with hands-on experience deploying and managing machine learning and large language model pipelines Expertise in cloud platforms (e.g., AWS, Azure) for ML workloads. Strong understanding of CI/CD principles and containerization technologies like Docker and Kubernetes. Familiarity with monitoring and alerting tools for ML systems (e.g., Prometheus, Grafana). Excellent communication, collaboration, and problem-solving skills. Ability to work independently and as part of a team. Passion for Generative AI and its potential to revolutionize various industries. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values diversity and inclusion, respect and integrity, customer focus, and innovation. For more information, visit www.genpact.com . Follow us on Twitter, Facebook, LinkedIn, and YouTube. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

About the Role Were looking for a Senior Java Backend Engineer (Gen AI- Voice and Conversation AI) to help architect and build the backend infrastructure powering next-gen AI voice agents. This is a high-impact role that combines backend expertise with cutting-edge AI integrations in a fast-paced startup environment. Key Responsibilities Own and evolve the architecture of our AI backend platform, built on Java and Spring Boot. Design scalable, secure, and low-latency systems that integrate with LLMs , TTS/STT , and RAG pipelines Lead development of RESTful APIs , microservices , and data orchestration Collaborate with AI/ML engineers to integrate inference layers and deploy real-time AI avatar experiences Optimize backend for performance, cost-efficiency , and reliability across cloud environments Drive implementation of CI/CD pipelines , testing, and DevOps best practices Mentor junior engineers and take end-to-end ownership of feature delivery Requirements 4-6 years of backend development experience in high-growth startups, especially in B2B space and AI first environments with Java (11/17) and Spring Boot Deep expertise in system design, microservices, event-driven architectures, and distributed systems Strong experience in cloud infrastructure AWS (preferred), Azure or GCP also welcome Experience working with AI teams or AI/ML product integrations Familiarity with integrating TTS/STT APIs, LLM endpoints , or asynchronous inference layers Proficient in working with PostgreSQL, MongoDB, Redis, and message queues like AWS SQS/SNS, Kafka or RabbitMQ Strong understanding of security, scalability, and performance tuning Startup or high-growth environment experience is a big plus Excellent problem-solving and communication skills Good to Have Exposure to MLOps and deploying ML models in production Experience with Docker , Kubernetes , ECS/EKS Familiarity with vector DBs , LangChain , and real-time streaming (WebSockets, voice protocols) Why You Should Join Build backend systems that enable real-time AI voice interviews and avatars Join a visionary team at the forefront of AI and voice tech innovation Work in a fast-paced, ownership-driven culture with zero bureaucracy Ship features that directly impact end-users from Day 1 Competitive salary + early-stage entry in a rapidly growing AI HRtech Enjoy full remote flexibility (initially), with long-term plans in Bangalore.

Java + AI/ML role required with at least 6+ years of industry experience on Java, Spring Boot, Spring Data & at least 2 years of AI/ML project / professional experience. Strong experience in building and consuming REST APIs and asynchronous messaging (Kafka/RabbitMQ). Working experience in integrating AI/ML models into Java services or calling external ML endpoints (REST/gRPC). Understanding of ML lifecycle: training, validation, inference, monitoring, and retraining. Familiarity with tools like TensorFlow, PyTorch, Scikit-Learn, or ONNX. Prior experience in domain-specific ML implementations (e.g., fraud detection, recommendation systems, NLP chatbots) Experience working with data formats like JSON, Parquet, Avro, and CSV. Solid understanding of database systems both SQL (PostgreSQL, MySQL) and NoSQL (Redis). Integrate machine learning models (batch and real-time) into backend systems and APIs. Optimize and automate AI/ML workflows using MLOps best practices. Monitor and manage model performance, versioning, and rollbacks. Collaborate with cross-functional teams (DevOps, SRE, Product Engineering) to ensure seamless deployment. Exposure to MLOps tools like MLflow, Kubeflow, or Seldon. Experience with any 1 of the cloud platforms, preferably AWS & Knowledge of observability tools & its metrics, events, logs, and traces (for e.g., Prometheus, Grafana, Open Telemetry, Splunk, Data Dog, App Dynamics, etc..).

We are looking for a GenAI/ML Engineer to design, develop, and deploy cutting-edge AI/ML models and Generative AI applications . This role involves working on large-scale enterprise use cases, implementing Large Language Models (LLMs) , building Agentic AI systems , and developing data ingestion pipelines . The ideal candidate should have hands-on experience with AI/ML development , Generative AI applications , and a strong foundation in deep learning , NLP , and MLOps practices. Key Responsibilities Design, develop , and deploy AI/ML models and Generative AI applications for various enterprise use cases. Implement and integrate Large Language Models (LLMs) using frameworks such as LangChain , LlamaIndex , and RAG pipelines . Develop Agentic AI systems capable of multi-step reasoning and autonomous decision-making . Create secure and scalable data ingestion pipelines for structured and unstructured data, enabling indexing, vector search, and advanced retrieval techniques. Collaborate with cross-functional teams (Data Engineers, Product Managers, Architects) to deploy AI solutions and enhance the AI stack. Build CI/CD pipelines for ML/GenAI workflows and support end-to-end MLOps practices. Leverage Azure and Databricks for training , serving , and monitoring AI models at scale. Required Qualifications & Skills (Mandatory) 4+ years of hands-on experience in AI/ML development , including Generative AI applications . Expertise in RAG , LLMs , and Agentic AI implementations. Strong experience with LangChain , LlamaIndex , or similar LLM orchestration frameworks. Proficiency in Python and key ML/DL libraries : TensorFlow , PyTorch , Scikit-learn . Solid foundation in Deep Learning , Natural Language Processing (NLP) , and Transformer-based architectures . Experience in building data ingestion , indexing , and retrieval pipelines for real-world enterprise use cases. Hands-on experience with Azure cloud services and Databricks . Proven track record in designing CI/CD pipelines and using MLOps tools like MLflow , DVC , or Kubeflow . Soft Skills Strong problem-solving and critical thinking ability. Excellent communication skills , with the ability to explain complex AI concepts to non-technical stakeholders. Ability to collaborate effectively in agile , cross-functional teams . A growth mindset , eager to explore and learn emerging technologies. Preferred Qualifications Familiarity with vector databases such as FAISS , Pinecone , or Weaviate . Experience with AutoGPT , CrewAI , or similar agent frameworks . Exposure to Azure OpenAI , Cognitive Search , or Databricks ML tools . Understanding of AI security , responsible AI , and model governance . Role Dimensions Design and implement innovative GenAI applications to address complex business problems. Work on large-scale, complex AI solutions in collaboration with cross-functional teams. Take ownership of the end-to-end AI pipeline , from model development to deployment and monitoring. Success Measures (KPIs) Successful deployment of AI and Generative AI applications . Optimization of data pipelines and model performance at scale. Contribution to the successful adoption of AI-driven solutions within enterprise use cases. Effective collaboration with cross-functional teams, ensuring smooth deployment of AI workflows. Competency Alignment AI/ML Development : Expertise in building and deploying scalable and efficient AI models. Generative AI : Strong hands-on experience in Generative AI , LLMs , and RAG frameworks. MLOps : Proficiency in designing and maintaining CI/CD pipelines and implementing MLOps practices . Cloud Platforms : Experience with Azure and Databricks for AI model training and serving.

We're hiring an experienced AI/ML Model Engineer to develop computer vision & AI-CAD solutions for enterprise clients. Work with U.S.-based teams to build & deploy scalable ML models. Requires 5+ yrs in ML, Python, TensorFlow/PyTorch & CAD expertise. Required Candidate profile ML engineer with 5+ years in computer vision and AI-driven CAD. Skilled in Python, TensorFlow, PyTorch, OpenCV. Delivers production models. Self-driven, team-oriented, thrives in fast-paced roles.

Job Description/Preferred Qualifications We are seeking a highly skilled and motivated MLOps Site Reliability Engineer (SRE) to join our team. In this role, you will be responsible for ensuring the reliability, scalability, and performance of our machine learning infrastructure. You will work closely with data scientists, machine learning engineers, and software developers to build and maintain robust and efficient systems that support our machine learning workflows. This position offers an exciting opportunity to work on cutting-edge technologies and make a significant impact on our organization's success. Responsibilities : Design, implement, and maintain scalable and reliable machine learning infrastructure. Collaborate with data scientists and machine learning engineers to deploy and manage machine learning models in production. Develop and maintain CI/CD pipelines for machine learning workflows. Monitor and optimize the performance of machine learning systems and infrastructure. Implement and manage automated testing and validation processes for machine learning models. Ensure the security and compliance of machine learning systems and data. Troubleshoot and resolve issues related to machine learning infrastructure and workflows. Document processes, procedures, and best practices for machine learning operations. Stay up-to-date with the latest developments in MLOps and related technologies. Required Qualifications: Bachelor's degree in Computer Science, Engineering, or a related field. Proven experience as a Site Reliability Engineer (SRE) or in a similar role. Strong knowledge of machine learning concepts and workflows. Proficiency in programming languages such as Python, Java, or Go. Experience with cloud platforms such as AWS, Azure, or Google Cloud. Familiarity with containerization technologies like Docker and Kubernetes. Experience with CI/CD tools such as Jenkins, GitLab CI, or CircleCI. Strong problem-solving skills and the ability to troubleshoot complex issues. Excellent communication and collaboration skills. Preferred Qualifications: Master's degree in Computer Science, Engineering, or a related field. Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Knowledge of data engineering and data pipeline tools such as Apache Spark, Apache Kafka, or Airflow. Experience with monitoring and logging tools such as Prometheus, Grafana, or ELK stack. Familiarity with infrastructure as code (IaC) tools like Terraform or Ansible. Experience with automated testing frameworks for machine learning models. Knowledge of security best practices for machine learning systems and data. Minimum Qualifications Master's Level Degree or Bachelor's Level Degree and related work experience of 2 years

Job Description/Preferred Qualifications We are seeking a highly skilled and motivated MLOps Site Reliability Engineer (SRE) to join our team. In this role, you will be responsible for ensuring the reliability, scalability, and performance of our machine learning infrastructure. You will work closely with data scientists, machine learning engineers, and software developers to build and maintain robust and efficient systems that support our machine learning workflows. This position offers an exciting opportunity to work on cutting-edge technologies and make a significant impact on our organization's success. Responsibilities : Design, implement, and maintain scalable and reliable machine learning infrastructure. Collaborate with data scientists and machine learning engineers to deploy and manage machine learning models in production. Develop and maintain CI/CD pipelines for machine learning workflows. Monitor and optimize the performance of machine learning systems and infrastructure. Implement and manage automated testing and validation processes for machine learning models. Ensure the security and compliance of machine learning systems and data. Troubleshoot and resolve issues related to machine learning infrastructure and workflows. Document processes, procedures, and best practices for machine learning operations. Stay up-to-date with the latest developments in MLOps and related technologies. Required Qualifications: Bachelor's degree in Computer Science, Engineering, or a related field. Proven experience as a Site Reliability Engineer (SRE) or in a similar role. Strong knowledge of machine learning concepts and workflows. Proficiency in programming languages such as Python, Java, or Go. Experience with cloud platforms such as AWS, Azure, or Google Cloud. Familiarity with containerization technologies like Docker and Kubernetes. Experience with CI/CD tools such as Jenkins, GitLab CI, or CircleCI. Strong problem-solving skills and the ability to troubleshoot complex issues. Excellent communication and collaboration skills. Preferred Qualifications: Master's degree in Computer Science, Engineering, or a related field. Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Knowledge of data engineering and data pipeline tools such as Apache Spark, Apache Kafka, or Airflow. Experience with monitoring and logging tools such as Prometheus, Grafana, or ELK stack. Familiarity with infrastructure as code (IaC) tools like Terraform or Ansible. Experience with automated testing frameworks for machine learning models. Knowledge of security best practices for machine learning systems and data. Minimum Qualifications Master's / Bachelor's Level Degree and related work experience of 2 years

You will be part of the Emerging Tech Proof of Concept Team at London Stock Exchange Group (LSEG), working within the Data and Analytics operations function. As a member of this team, you will be responsible for delivering and supporting various Data Science capabilities. Operating in an Agile manner, your focus will be on prioritizing and delivering value efficiently while also considering long-term initiatives and technical capabilities to enhance our service offerings. Your role will involve owning the technical solutions developed by the team, developing functional modules for wider usage, and collaborating with cross-functional teams to implement innovative solutions. You will be responsible for creating Proof of Concepts and Minimum Viable Products (MVP) to validate different approaches for various use cases. Additionally, you will develop codebases and modules to support the deployment of AI/ML models using relevant technologies. Collaboration with Architects and Cloud engineers will be essential for integrating the developed solutions with Technology platforms. You will also work closely with the team to establish and oversee the evaluation criteria of POCs and MVPs, and provide support in other relevant areas when needed. Furthermore, you will collaborate with Operations and Technology teams to ensure successful project outcomes. To excel in this role, you should possess extensive experience as a Machine Learning Engineer with a track record of working on projects across all stages of the ML Lifecycle. Your expertise should include developing scalable solutions for use cases in Extraction and Reasoning using Python programming and SQL. Knowledge of MLOps approaches, AWS services, cloud environments, and AI/ML solution development and deployment will be crucial. Strong analytical, problem-solving, communication, and presentation skills are also required. By joining LSEG, a leading global financial markets infrastructure and data provider, you will become part of a diverse workforce that values individuality and encourages new ideas. The company is committed to sustainability and driving economic growth by supporting the transition to net zero and creating inclusive economic opportunities. As an employee, you will have access to a range of benefits including healthcare, retirement planning, paid volunteering days, and wellbeing initiatives. Please be aware of LSEG's privacy notice which describes the personal information the company may hold about you, its usage, your rights, and how to contact LSEG as a data subject. If you are a Recruitment Agency Partner, it is your responsibility to ensure that candidates applying to LSEG are informed about this privacy notice.,

Vimaan is looking to onboard multiple Machine Learning Engineers in Bengaluru, India to drive the development of computer vision and machine learning algorithms to power our cutting-edge wall-to-wall warehouse inventory tracking and verification platform. This is a unique opportunity to exploit a treasure cove of unseen real-world data coming from a multi-camera perception system and develop large-scale computer vision and deep learning models to build a product that creates a disproportionate value for the warehouse industry. The role involves hands-on CV/ML software development and deployment from understanding the product requirements, defining Computer Vision functional specs to designing, developing, and deploying CV/ML models in production at scale. The ideal candidate for the Machine Learning Engineer position should have an MS in computer vision, machine learning, AI, applied mathematics, data science, or related technical fields, or a BS with 3+ years of experience in Computer Vision/Machine Learning. They should possess hands-on experience in developing new learning algorithms for computer vision tasks such as object detection, object tracking, instance segmentation, activity detection, depth estimation, optical flow, multi-view geometry, domain adaptation, adversarial and generative models, as well as representational learning with varying amounts of data. Knowledge of current deep learning literature and the mathematical foundations of machine learning is essential. Experience with popular object detection frameworks such as YOLO, SSD, or Faster R-CNN is considered a plus. The candidate should have the ability to train and debug deep learning systems, gain deep insights into data characteristics, and map those to appropriate model architectures. Experience working with inputs from multiple cameras and input modes is advantageous, as is experience in AI Infrastructure, Machine Learning Accelerators, On-Device Optimization, and training and deploying deep learning models on GPU-accelerated platforms. Strong programming skills with Python and experience with ML/DL frameworks like Tensorflow, Pytorch, etc., are required. Prior experience in deploying machine learning models in production environments, working with cloud platforms (e.g., AWS, Azure, Google Cloud), and familiarity with data pre-processing, augmentation, and visualization tools and libraries are necessary. The ideal candidate should be highly motivated, passionate, possess a strong work ethic, and be able to work effectively in a team or independently under supervision in a matrix management environment. Effective communication skills, problem-solving abilities, attention to detail, and a passion for staying at the forefront of technology advancements in machine learning and computer vision are key attributes. They should be able to work in a fast-paced, high-pressure startup environment, adapt to rapidly changing requirements, and convey complex technical concepts to non-technical stakeholders. The Machine Learning Engineer will be responsible for researching, designing, and developing machine learning algorithms and models for various tasks of detection, recognition, and classification for warehouse inventory management. They will implement and optimize deep learning architectures, explore techniques like transfer learning and data augmentation, guide annotation teams, curate and pre-process annotated datasets, collaborate with MLOps for integrating machine learning models into production systems, and conduct thorough performance analysis and evaluation of models using appropriate metrics and tools. It is essential for the Machine Learning Engineer to stay up-to-date with the latest advancements in machine learning and computer vision research and integrate relevant findings into the solutions developed at Vimaan. ABOUT VIMAAN Headquartered in Silicon Valley, with team members around the world, Vimaan is comprised of computer vision and hardware technologists, as well as warehousing domain experts with a successful history in technology startups. Vimaan's primary mission is to deliver computer vision and machine learning solutions to solve long-standing inventory visibility, accuracy, and quality challenges in the supply chain.,

Appnext offers end-to-end discovery solutions covering all the touchpoints users have with their devices. Thanks to Appnext's direct partnerships with top OEM brands and carriers, user engagement is achieved from the moment they personalize their device for the first time and throughout their daily mobile journey. Appnext Timeline, a patented behavioral analytics technology, is uniquely capable of predicting the apps users are likely to need next. This innovative solution means app developers and marketers can seamlessly engage with users directly on their smartphones through personalized, contextual recommendations. Established in 2012 and now with 12 offices globally, Appnext is the fastest-growing and largest independent mobile discovery platform in emerging markets. As a Machine Learning Engineer, you will be in charge of building end-to-end machine learning pipelines that operate at a huge scale, from data investigation, ingestions and model training to deployment, monitoring, and continuous optimization. You will ensure that each pipeline delivers measurable impact through experimentation, high-throughput inference, and seamless integration with business-critical systems. This job combines 70% machine learning engineering and 30% algorithm engineering and data science. We're seeking an Adtech pro who thrives in a team environment, possesses exceptional communication and analytical skills, and can navigate high-pressure demands of delivering results, taking ownership, and leveraging sales opportunities. Responsibilities: Build ML pipelines that train on real big data and perform on a massive scale. Handle a massive responsibility, Advertise on lucrative placement (Samsung appstore, Xiaomi phones, TrueCaller). Train models that will make billions of daily predictions and affect hundreds of millions users. Optimize and discover the best solution algorithm to data problems, from implementing exotic losses to efficient grid search. Validate and test everything. Every step should be measured and chosen via AB testing. Use of observability tools. Own your experiments and your pipelines. Be Frugal. Optimize the business solution at minimal cost. Advocate for AI. Be the voice of data science and machine learning, answering business needs. Build future products involving agentic AI and data science. Affect millions of users every instant and handle massive scale Requirements: MSc in CS/EE/STEM with at least 5 years of proven experience (or BSc with equivalent experience) as a Machine Learning Engineer: strong focus on MLOps, data analytics, software engineering, and applied data science- Must Hyper communicator: Ability to work with minimal supervision and maximal transparency. Must understand requirements rigorously, while frequently giving an efficient honest picture of his/hers work progress and results. Flawless verbal English- Must Strong problem-solving skills, drive projects from concept to production, working incrementally and smart. Ability to own features end-to-end, theory, implementation, and measurement. Articulate data-driven communication is also a must. Deep understanding of machine learning, including the internals of all important ML models and ML methodologies. Strong real experience in Python, and at least one other programming language (C#, C++, Java, Go). Ability to write efficient, clear, and resilient production-grade code. Flawless in SQL. Strong background in probability and statistics. Experience with tools and ML models Experience with conducting A/B test. Experience with using cloud providers and services (AWS) and python frameworks: TensorFlow/PyTorch, Numpy, Pandas, SKLearn (Airflow, MLflow, Transformers, ONNX, Kafka are a plus). AI/LLMs assistance: Candidates have to hold all skills independently without using AI assist. With that candidates are expected to use AI effectively, safely and transparently. Preferred: Deep Knowledge in ML aspects including ML Theory, Optimization, Deep learning tinkering, RL, Uncertainty quantification, NLP, classical machine learning, performance measurement. Prompt engineering and Agentic workflows experience Web development skills Publication in leading machine learning conferences and/or medium blogs.,

As a Machine Learning Engineer at ClearTrail, you will be a part of a team dedicated to developing solutions that empower law enforcement and federal agencies globally to keep their people, places, and communities safe. With over 21 years of experience in safeguarding nations and enriching lives, ClearTrail is leading the way in the future of intelligence gathering through artificial intelligence and machine learning-based lawful interception & communication analytics solutions. Your role will involve developing end-to-end machine learning pipelines for a variety of analytics problems, refining models, and implementing solutions. You will be responsible for communicating results to both technical and non-technical audiences, providing expertise in large language models (LLMs), such as OpenAI models, and utilizing retrieval augmented generation techniques to enhance LLM performance. Additionally, you will stay updated with the latest advancements in AI, demonstrate strong problem-solving and code debugging skills, and have practical experience with proprietary and open-source generative AI models like transformers and GPT models. The ideal candidate for this position should have 2-4 years of experience as a Machine Learning Engineer with expertise in LLMs. You should possess a Bachelor's degree in computer science & engineering, sound theoretical and practical knowledge of machine learning algorithms, and hands-on experience with LLM applications. Mandatory skills include proficiency in Python, Scikit-Learn, PyTorch, LangChain, and Transformers libraries, as well as experience in exploratory data analysis, neural networks, hyperparameter tuning, model deployment, and SQL. Join us at ClearTrail in Indore, M, and be a part of a dynamic team that is shaping the future of intelligence gathering and making a difference in the world.,

As a Data Scientist at UST, you will independently develop data-driven solutions to tackle complex business challenges by utilizing analytical, statistical, and programming skills to collect, analyze, and interpret large datasets under supervision. Your role involves working closely with stakeholders across the organization to identify opportunities for leveraging customer data in creating models that generate valuable business insights. You will be responsible for creating new experimental frameworks, building automated tools for data collection, correlating similar datasets, and deriving actionable results. Additionally, you will develop predictive models and machine learning algorithms to analyze vast amounts of information, uncover trends, and patterns. By mining and analyzing data from company databases, you will drive optimization and improvement in product development, marketing techniques, and business strategies. Moreover, you will be expected to create processes and tools to monitor and analyze model performance, data accuracy, and develop data visualization and illustrations to address business problems effectively. Your role will also involve using predictive modeling to enhance and optimize customer experiences and other business outcomes. Collaboration with different functional teams to implement models and monitor outcomes is essential. You will be required to set and provide feedback on FAST goals for reportees. Key responsibilities include applying statistical techniques like regression, properties of distributions, and statistical tests to analyze data, as well as utilizing machine learning techniques such as clustering, decision tree learning, and artificial neural networks for data analysis. Moreover, you will be creating advanced algorithms and statistics through regression, simulation, scenario analysis, and modeling. In terms of data visualization, you will visualize and present data for stakeholders using tools like Periscope, Business Objects, D3, ggplot, etc. You will oversee the activities of analyst personnel, ensuring efficient execution of their duties, while mining the business's database for critical insights and communicating findings to relevant departments. Other expectations include creating efficient and reusable code for data improvement, manipulation, and analysis, managing project codebase through version control tools like git and bitbucket, and creating reports depicting trends and behaviors from analyzed data. You will also be involved in training end users on new reports and dashboards, documenting your work, conducting peer reviews, managing knowledge, and reporting task status. The ideal candidate will possess excellent pattern recognition and predictive modeling skills, a strong background in data mining and statistical analysis, expertise in machine learning techniques, and advanced algorithm creation. Moreover, analytical, communication, critical thinking, attention to detail, mathematical, and interpersonal skills are crucial for success in this role. Proficiency in programming languages such as Java, Python, R, web services like Redshift and S3, statistical and data mining techniques, computing tools, analytical languages, data visualization software, mathematics, spreadsheet tools, DBMS, operating systems, and project management tools is required. Additionally, a strong understanding of statistical concepts, SQL, machine learning (Regression and Classification), deep learning (ANN, RNN, CNN), advanced NLP, computer vision, Gen AI/LLM, AWS Sagemaker/Azure ML/Google Vertex AI, and basic implementation experience of Docker, Kubernetes, kubeflow, MLOps, Python (numpy, panda, sklearn, streamlit, matplotlib, seaborn) is essential for this role.,

As a research scientist at AryaXAI, you will have the unique opportunity to be part of a team that is revolutionizing the field of AI. Our mission is to develop explainable, safe, and scalable AI systems that empower researchers, engineers, and organizations while ensuring transparency and safety. Our team at AryaXAI is driven by a shared passion for innovation, collaboration, and excellence. In our flat organizational structure, everyone actively contributes to our mission, embodying values of curiosity, initiative, and outstanding performance. In this role, you will tackle advanced challenges in ML explainability, safety, and alignment. You will have the flexibility to specialize in various ML/DL areas that address these challenges, and develop new techniques around ML Observability & Alignment. Collaborating with MLEs and SDEs, you will lead the rollout of features and ensure their quality and stability. Additionally, you will be responsible for creating and maintaining technical and product documentation. To excel in this position, you should have a strong academic background in machine learning and deep learning concepts. Hands-on experience with frameworks like Tensorflow and Pytorch is essential. An enthusiasm for working on diverse DL problems involving different data sets (textual, tabular, categorical, images) is crucial. Proficiency in deploying code in cloud/on-premise environments, along with solid knowledge of MLOps and productionizing ML models, is required. Moreover, prior experience in ML explainability methods such as LRP, SHAPE, LIME, IG, CEM, and at least 2 years of hands-on experience in Deep Learning or Machine Learning are preferred. Hands-on experience in implementing techniques like Transformer models, GANs, and other deep learning models will be beneficial for this role.,

As a Machine Learning Engineer, your primary responsibility will be to design and implement end-to-end ML pipelines using GCP services and ETL tools. You will be deploying and maintaining predictive ML models through containerization (Docker) and orchestration (Kubernetes). It is essential for you to implement MLOps practices including CI/CD pipelines using Git. Additionally, you will create and maintain technical architecture diagrams for GCP service implementations and develop frontend applications that integrate with ML and AI backend services. Your expertise will be crucial in optimizing big data processing workflows and improving ML model performance. To excel in this role, you must possess a strong background in Machine Learning and Deep Learning concepts. Extensive experience with GCP services, particularly AI/ML offerings, is a must. Proficiency in MLOps practices and tools is highly desirable. Hands-on experience with Docker, Kubernetes, and Git is required for this position. Your familiarity with frontend development and API integration will be beneficial. Knowledge of big data processing and analytics is essential. Furthermore, your ability to create clear technical documentation and architecture diagrams will be a significant asset to the team. Preferred qualifications for this role include Google Cloud certifications, experience with AI and GenAI models and applications, background in full-stack development, understanding of microservices architecture, experience with data pipeline optimization, as well as knowledge of Python, HTML, and Javascript. Join our team and contribute to cutting-edge projects that leverage machine learning technologies in a cloud-based environment.,

Siemens Energy is looking for a highly skilled and experienced Senior MLOps Engineer to join the Digital Core function and contribute significantly to the data architecture and strategy within the organization. You will work closely with stakeholders to develop our Machine Learning environment, collaborating with business stakeholders and other teams to prioritize backlog items, offer consultancy on AI ML solutions, support test automation, build CI CD pipelines, and work on PoCs/MVPs using various hyperscale offerings. If you are passionate about the environment and climate change and eager to be a part of the energy transition future, then the Siemens Energy Data Analytics & AI team is the place for you. We are seeking innovative, enthusiastic, and versatile data, digital, and AI professionals to drive us forward on this exciting journey of energy transformation. Your responsibilities will include onboarding new AI ML use cases in AWS / Google Cloud Platform, defining MLOps architecture for AWS/ GCP/ Cloud Agnostic, working with AI ML services like AWS Sagemaker and GCP AutoML, developing PoCs / MVPs using AWS / GCP and other MLOps services, implementing CI CD pipelines using GitLab CI, writing Infrastructure as code with AWS CDK scripts, providing consultancy to stakeholders on AI ML solutions, supporting test automation, and deploying code base to production environments. To be successful in this role, you should have a Bachelor's degree in Computer Science, Mathematics, Engineering, Physics, or related fields (a Master's degree is a plus), around 10 years of hands-on experience in ML / AI development and Operations, expertise in ML Life Cycle and MLOps, proficiency in Python coding and Linux administration, experience with CI CD pipelines and DevOps processes, familiarity with JIRA and Confluence, and excellent interpersonal and communication skills. Certification in AWS or GCP in ML AI area is preferred. The Data Platforms and Services organization at Siemens Energy is committed to becoming a data-driven organization to support customers in transitioning to a more sustainable world. By using innovative technologies and treating data as a strategic asset, we aim to make sustainable, reliable, and affordable energy a reality. Siemens Energy values diversity and inclusion, welcoming applications from individuals of all backgrounds. We believe that through diversity, we generate power, and our combined creative energy is fueled by over 130 nationalities. We celebrate character and do not discriminate based on differences, upholding equal opportunities for all. If you are ready to make an impact in shaping the future of energy and are committed to innovation, decarbonization, and energy transformation, join us at Siemens Energy. For more information about Siemens Energy and our commitment to diversity, visit our website: https://www.siemens-energy.com/employeevideo To explore job opportunities at Siemens Energy, visit: https://jobs.siemens-energy.com/jobs,

As a ML Engineer/Data Scientist at Innova ESI in Bengaluru, you will be responsible for leveraging your strong background in Computer Science and Algorithms to work on pattern recognition, neural networks, algorithms, and statistical methods in order to deliver end-to-end data solutions. Your role will involve collaborating in cross-functional teams to drive digital transformation through innovative and sustainable IT solutions. You should have a deep understanding of machine learning and NLP, along with commercial experience in building and deploying LLM solutions. With 4-8 years of relevant experience, you are expected to demonstrate exceptional coding ability, particularly in Python, and be familiar with ML tools and libraries like TensorFlow, PyTorch, pandas, and scikit-learn. Your proficiency in Pattern Recognition and Neural Networks, combined with knowledge of Statistics and its application in data analysis, will be key in working with complex algorithms and data models. In addition, you should have a strong understanding of MLOps best practices and experience in deploying LLM applications to production at scale. As a problem solver and self-starter, you enjoy tackling difficult problems and finding optimal solutions independently as well as in a collaborative team environment. Your strong communication skills will enable you to effectively articulate complex technical concepts to non-technical stakeholders. This full-time hybrid role offers flexibility for some remote work while being primarily based in Bengaluru. If you meet the qualifications and are excited about driving digital transformation through innovative data solutions, we encourage you to share your resume with us at jaya.sharma@innovaesi.com.,

As a Machine Learning Engineer specializing in Computer Vision, you will play a crucial role in designing, developing, and deploying cutting-edge computer vision models and algorithms for real-world robotic applications. Working alongside a talented team, you will utilize state-of-the-art deep learning techniques to solve complex vision problems ranging from object detection to image segmentation and 3D perception. Your contributions will directly influence the evolution of intelligent systems within the field of robotics. This position is based on-site in Pune and requires immediate availability for joining within one month. Qualifications: - Educational Background: B.Tech., B.S., or B.E. in CSE, EE, ECE, ME, Data Science, AI, or related fields with a minimum of 2 years of hands-on experience in Computer Vision and Machine Learning. Alternatively, an M.S. or M.Tech. in the same disciplines with 2 years of practical experience in Computer Vision and Python programming. - Technical Expertise: You should possess strong experience in developing deep learning models and algorithms for various computer vision tasks, including object detection, image classification, segmentation, and keypoint detection. Proficiency in Python and ML frameworks like PyTorch, TensorFlow, or Keras is essential. Additionally, experience with OpenCV for image processing and computer vision pipelines is required. A solid understanding of convolutional neural networks (CNNs) and other vision-specific architectures such as YOLO, Mask R-CNN, and EfficientNet is expected. Ability to build, test, and deploy robust models using PyTest or PyUnit testing frameworks is necessary. Hands-on experience with data augmentation, transformation, and preprocessing techniques for visual data is also a key requirement. Familiarity with version control using Git is a plus. - Desirable Skills: Experience with 3D vision, stereo vision, or depth sensing technologies will be advantageous. Familiarity with ROS2 for integrating vision systems into robotic platforms, understanding of sensor fusion techniques (e.g., LiDAR, depth cameras, IMUs), exposure to MLOps for deploying and maintaining computer vision models in production environments, knowledge of CMake for building and integrating machine learning and vision-based solutions, experience with cloud-based solutions for computer vision, and ability to work with CUDA, GPU-accelerated libraries, and distributed computing environments are desirable skills. Location: This role is on-site in Pune, India, and immediate availability for joining is required. Why Join Us - Shape the future of robotics and AI by focusing on state-of-the-art computer vision applications. - Work in a dynamic and collaborative environment with a team of highly motivated engineers. - Competitive salary and benefits package, including performance-based incentives. - Opportunities for growth and professional development, including mentorship from industry experts. If you are passionate about leveraging deep learning and computer vision to develop intelligent systems that perceive and interact with the world, we look forward to hearing from you!,

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

As an AI Ops Expert, you will be responsible for the delivery of projects with defined quality standards within set timelines and budget constraints. Your role will involve managing the AI model lifecycle, versioning, and monitoring in production environments. You will be tasked with building resilient MLOps pipelines and ensuring adherence to governance standards. Additionally, you will design, implement, and oversee AIops solutions to automate and optimize AI/ML workflows. Collaboration with data scientists, engineers, and stakeholders will be essential to ensure seamless integration of AI/ML models into production systems. Monitoring and maintaining the health and performance of AI/ML systems, as well as developing and maintaining CI/CD pipelines for AI/ML models, will also be part of your responsibilities. Troubleshooting and resolving issues related to AI/ML infrastructure and workflows will require your expertise, along with staying updated on the latest AI Ops, MLOps, and Kubernetes tools and technologies. To be successful in this role, you must possess a Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field, along with at least 8 years of relevant experience. Your proven experience in AIops, MLOps, or related fields will be crucial. Proficiency in Python and hands-on experience with Fast API are required, as well as strong expertise in Docker and Kubernetes (or AKS). Familiarity with MS Azure and its AI/ML services, including Azure ML Flow, is essential. Additionally, you should be proficient in using DevContainer for development and have knowledge of CI/CD tools like Jenkins, Argo CD, Helm, GitHub Actions, or Azure DevOps. Experience with containerization and orchestration tools, Infrastructure as Code (Terraform or equivalent), strong problem-solving skills, and excellent communication and collaboration abilities are also necessary. Preferred skills for this role include experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn, as well as familiarity with data engineering tools like Apache Kafka, Apache Spark, or similar. Knowledge of monitoring and logging tools such as Prometheus, Grafana, or ELK stack, along with an understanding of data versioning tools like DVC or MLflow, would be advantageous. Proficiency in Azure-specific tools and services like Azure Machine Learning (Azure ML), Azure DevOps, Azure Kubernetes Service (AKS), Azure Functions, Azure Logic Apps, Azure Data Factory, Azure Monitor, and Application Insights is also preferred. Joining our team at Socit Gnrale will provide you with the opportunity to be part of a dynamic environment where your contributions can make a positive impact on the future. You will have the chance to innovate, collaborate, and grow in a supportive and stimulating setting. Our commitment to diversity and inclusion, as well as our focus on ESG principles and responsible practices, ensures that you will have the opportunity to contribute meaningfully to various initiatives and projects aimed at creating a better future for all. If you are looking to be directly involved, develop your expertise, and be part of a team that values collaboration and innovation, you will find a welcoming and fulfilling environment with us at Socit Gnrale.,

As a Gen AI Engineer at StatusNeo, you will be responsible for developing, optimizing, and deploying AI models and solutions with a focus on Generative AI, Prompt Engineering, Retrieval-Augmented Generation (RAG) models, and Large Language Models (LLMs). You will collaborate closely with cross-functional teams to design and implement scalable AI solutions on various cloud platforms. Key Responsibilities: - AI Model Development: Design, train, and fine-tune generative AI models, LLMs, and RAG models to address specific business use cases. - Prompt Engineering: Develop, test, and optimize prompts to enhance the performance and accuracy of AI models in generating desired outputs. - Cloud Expertise: Deploy and manage AI models on cloud platforms (e.g., AWS, Azure, GCP) ensuring scalability, security, and cost-efficiency. - Data Management: Collaborate with data scientists and engineers to ensure high-quality data ingestion, preprocessing, and feature engineering. - Model Evaluation & Tuning: Continuously monitor and evaluate model performance, making adjustments to improve accuracy and efficiency. - Innovation: Stay up-to-date with the latest advancements in AI, LLMs, and cloud technologies, and incorporate new techniques and tools into the development process. - Collaboration: Work closely with product managers, software engineers, and other stakeholders to integrate AI solutions into products and services. - Documentation: Maintain comprehensive documentation of models, algorithms, and development processes to ensure transparency and reproducibility. Qualifications: - Education: Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or a related field. - Experience: Proven experience in developing and deploying AI models, particularly in Generative AI, LLMs, and RAG models. Hands-on experience with cloud platforms like AWS, Azure, or GCP for AI/ML workloads. Strong background in Prompt Engineering and AI model optimization techniques. - Technical Skills: Proficiency in programming languages such as Python, TensorFlow, PyTorch, or similar frameworks. Experience with NLP, machine learning algorithms, and data preprocessing. Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes) is a plus. Familiarity with MLOps practices and tools for continuous integration and deployment. - Soft Skills: Strong problem-solving skills and the ability to work in a fast-paced environment. Excellent communication and teamwork abilities. Eagerness to learn and adapt to new technologies and methodologies.,

As an AI-ML Architect, you will leverage your 10+ years of experience in developing systems software on Windows or Linux to build, train, and optimize neural network data analytics applications. Your hands-on expertise with Deep Learning frameworks such as Pytorch, TensorFlow, or Caffe will be instrumental in enhancing network performance at kernel level for scalability across hardware. You will play a crucial role in developing, training, and tuning Deep Learning software/models while also exploring techniques like Reinforcement Learning, Transfer Learning, and Federated Learning. Your proficiency in Python programming and C/C++ programming, coupled with solid web service development experience, especially in REST API, will enable you to automate deployment, management, scaling, and networking utilizing Dockers and Kubernetes. Experience with Open Vino, One API DPC++, OpenCL, CUDA programming is preferred. Your familiarity with MLOps, Deep learning infrastructure, microservices architecture, and cloud/distributed infrastructure will be key in designing cutting-edge AI solutions. If you are passionate about AI and possess a strong technical background, this role in Bangalore offers an exciting opportunity to drive innovation in AI-ML architecture and contribute to the development of advanced technologies.,

As an IT Manager specializing in Generative AI Engineering at Alexion, you will lead the development and refinement of cutting-edge Generative AI systems to tackle complex business problems. You will work closely with the IT Director of Data Science to implement state-of-the-art Machine Learning solutions, focusing on Generative AI. Your role will involve contributing to the full lifecycle development of Generative AI agents, integrating pre-trained models into custom applications, and designing interactive systems for dynamic content. Additionally, you will be responsible for maintaining MLOps infrastructure, implementing user interfaces for seamless interaction with Generative AI functionalities, and monitoring the operational health of AI applications in production. Collaboration with senior engineers, stakeholders, and cross-functional teams will be essential to gather feedback, improve application features, and ensure ethical use of Generative AI models within the Machine Learning ecosystem. To excel in this role, you should hold a Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field. With at least 3 years of experience in Machine Learning, data science, or software development, you should possess a strong understanding of ML Engineering concepts and tools, Python programming, cloud computing platforms like AWS, Azure, or GCP, and agile methodologies. Communication, collaboration, analytical, and problem-solving skills are crucial for success in this dynamic and innovative environment. Desirable skills include experience in the pharmaceutical industry, a Master's degree in a related field, and a deep knowledge of AI techniques such as NLP, optimization, and deep learning. By joining Alexion, you will have the opportunity to work in an environment where innovation thrives, impacting patients" lives with life-changing medicines. With a commitment to rare diseases and a global presence, AstraZeneca offers a unique and ambitious world for your career growth and development. If you are proactive, eager to learn, and ready to make a difference in the field of Generative AI Engineering, apply now to join us on this exciting journey at Alexion. Date Posted: 18-Jul-2025 Closing Date: 30-Jul-2025,

You are a technology-led healthcare solutions provider with a strong purpose to enable healthcare organizations to be future-ready. You offer accelerated global growth opportunities for individuals who are bold, industrious, and nimble. At Indegene, you provide a unique career experience that celebrates entrepreneurship and is driven by passion, innovation, collaboration, and empathy. Indegene values the importance of the early years of your career, recognizing that they lay the foundation for your professional journey. By joining the team, you can expect a differentiated career experience that exposes you to the dynamic intersection of healthcare and technology. You will have the opportunity to be mentored by industry experts and grow alongside the company's high-speed expansion on a global scale. As a Competency Leader, your role involves leading the design, development, and deployment of advanced AI and Generative AI solutions that bring substantial business value to pharma clients. You should possess extensive hands-on experience with AI/ML frameworks, cloud platforms, MLOps, and a deep understanding of GenAI technologies. Key Responsibilities: - Design, develop, and optimize AI/ML models for practical applications ensuring high performance, scalability, and reliability. - Innovate using advanced GenAI technologies to address complex business challenges. - Implement and manage end-to-end MLOps pipelines, including CI/CD, model monitoring, retraining workflows, and versioning. - Architect and deploy scalable, cost-effective AI/ML solutions on cloud platforms such as AWS and Azure. - Collaborate with cross-functional stakeholders to align AI solutions with business objectives. - Mentor and guide junior engineers, fostering innovation and adherence to best practices in AI/ML development and deployment. - Develop and train Generative AI models. - Perform data analysis and prepare data for AI model training. - Integrate AI models with Snowflake, AWS, and other systems. Required Knowledge: - 10+ years of experience in AI/ML development and deployment, including leadership roles. - Good knowledge of machine learning and Generative AI, especially content generation using AWS Bedrock and OpenAI-based models. - Proficiency in working with GenAI tools and technologies such as LLMs, RAG, OpenAI APIs, LangChain, Streamlit, and vector databases. - Experience in building scalable (Gen) AI applications on AWS. - Strong background and understanding of vector databases. - Good knowledge of Python for data science and streamlit for rapid deployment of prototypes. - Experience working in an agile environment. - Experience in setting up and using CI/CD pipelines as well as writing software in a test-driven fashion. - Experience in building (Gen) AI solutions on Snowflake is a plus. - Experience with Agentic AI build. Key Skills: Python, AI/ML Expertise, Deep Learning, NLP, MLOps, Cloud Platforms (AWS, Azure), GenAI (LLM, RAG, OpenAI), LangChain, Streamlit, API Architecture, Leadership, Business-Aligned Problem Solving, Prompt Engineering, Knowledge of Vector Databases. EQUAL OPPORTUNITY If you are excited about the prospect of contributing to cutting-edge AI solutions in the healthcare industry and are ready to take on a challenging yet rewarding role, we encourage you to apply.,

The Specialized Analytics Manager provides full leadership and supervisory responsibility. You will provide operational/service leadership and direction to team(s). You will apply in-depth disciplinary knowledge through provision of value-added perspectives or advisory services. You may contribute to the development of new techniques, models, and plans within the area of expertise. Excellent communication and diplomacy skills are required for this role. You will generally have responsibility for volume, quality, timeliness of end results, and shared responsibility for planning and budgets. Your work will affect an entire area, which eventually affects the overall performance and effectiveness of the sub-function/job family. You will have full supervisory responsibility, ensuring motivation and development of the team through professional leadership. This will include duties such as performance evaluation, compensation, hiring, disciplinary and terminations, as well as direction of daily tasks and responsibilities. The Data Science Analyst is a developing professional role within the GWFO team. In this role, you will apply specialized knowledge in machine learning, statistical modeling, and data analysis to monitor, assess, analyze, and evaluate processes and data. You will identify opportunities to leverage advanced analytics to improve business outcomes, automate processes, and generate actionable insights. Additionally, you will contribute to the development and deployment of innovative AI solutions, including generative AI and agentic AI applications. You will work with cross-functional stakeholders to gather and process operational data from various sources to examine past business performance and identify areas for improvement. As a successful candidate, you should ideally have 7+ years of relevant experience in data science, machine learning, or a related field. You should possess advanced process management skills, be organized and detail-oriented, curious about learning and developing new skill sets, particularly in the area of artificial intelligence, have a positive outlook with a can-do mindset, and strong programming skills in Python and proficiency in relevant data science libraries such as scikit-learn, TensorFlow, PyTorch, and Transformers. Experience with statistical modeling techniques, building GenAI solutions, agentic AI frameworks, and data visualization tools such as Tableau or Power BI is required. Strong logical reasoning capabilities, willingness to learn new skills, and good communication and presentation skills are also essential. You should have a Bachelors/University degree or equivalent experience. This job description provides a high-level review of the types of work performed, and other job-related duties may be assigned as required. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity, review Accessibility at Citi. View Citis EEO Policy Statement and the Know Your Rights poster.,

You will be joining ClearTrail as a ML Engineer with 6-10 years of experience in Machine Learning and LLM skill set. ClearTrail is focused on developing solutions to empower those dedicated to ensuring the safety of people, places, and communities globally. With over 23 years of experience, ClearTrail has been a trusted partner of law enforcement and federal agencies worldwide, actively contributing to safeguarding nations and enriching lives. ClearTrail is at the forefront of intelligence gathering, utilizing artificial intelligence and machine learning based lawful interception & communication analytics solutions to address some of the world's most complex challenges. As an ML Engineer at ClearTrail, you will be responsible for developing an end-to-end machine learning pipeline, encompassing model development, refinement, and implementation for various analytics problems. Your role will involve effectively communicating results to a diverse range of technical and non-technical audiences. Additionally, you will leverage your expertise in LLM to tackle problems using cutting-edge language models and off-the-shelf LLM services such as OpenAI models. Your responsibilities will also include staying updated with the latest advancements in AI, problem-solving, code debugging, and practical experience in working with large language and generative AI models, including transformers and GPT models. Qualifications for this role include a Bachelor's degree in computer science & engineering, along with 6-10 years of proven experience as a Machine Learning Engineer or similar role with LLM skill set. You should possess sound theoretical and practical knowledge of machine learning algorithms and hands-on experience with LLM applications. Proficiency in Python, Scikit-Learn, PyTorch, LangChain, and Transformers libraries is essential, along with expertise in techniques such as Exploratory Data Analysis, Machine Learning, Neural Networks, Hyperparameter tuning, Model performance metrics, and Model Deployment. Practical knowledge of LLM and its finetuning is also a mandatory requirement. While not mandatory, it would be advantageous to have skills in Deep Learning, MLOps, and SQL. By joining ClearTrail, you will have the opportunity to contribute to the future of intelligence gathering and play a vital role in developing innovative solutions to address complex challenges in the realm of security and safety.,