78 Model Monitoring Jobs - Page 2

You are seeking an AI Engineer (Level 2 & 3) with a deep passion for exploring AI technologies, particularly Large Language Models (LLMs) and advanced NLP techniques. The ideal candidate will have a strong foundation in deep learning architectures and experience with state-of-the-art AI frameworks. In this role, you will work on developing and deploying intelligent applications that solve real-world problems for our clients, leveraging tools like LangChain, Hugging Face, and OpenAI APIs. Your responsibilities will include designing and developing AI solutions focusing on large language models, experimenting with state-of-the-art Transformer architectures to address complex language understanding and generation tasks. You will leverage modern AI frameworks and tools to develop, fine-tune, and integrate LLMs into applications, ensuring models are optimized and efficient for production use. Implement and enhance NLP capabilities like text generation, summarization, and retrieval-augmented generation (RAG) to provide intelligent and contextually aware features in solutions. Craft effective prompts and fine-tune LLMs to improve model performance for specific domains and use cases. Deploy and scale models in production environments, implementing MLOps best practices for robust, repeatable model deployments. Utilize cloud services for model training, deployment, and infrastructure management, optimizing resources to handle large-scale training and inference efficiently. Continuously optimize model performance and implement scaling strategies to handle large datasets and high-volume usage. Collaborate with cross-functional teams to integrate AI capabilities into products, ensuring AI systems meet client needs and quality standards. Stay up-to-date with the latest AI research, papers, and trends in the industry, experimenting with new algorithms, models, and techniques to keep solutions at the cutting edge. You should have a Bachelor's or Master's degree in Computer Science, Engineering, or a related field, plus 4+ years of hands-on experience in AI/ML engineering or a similar role. Strong foundation in deep learning and NLP, experience in transformer-based architectures and large language models is required. Proficiency in Python programming and experience with major AI/ML frameworks and libraries is necessary. Proven experience in developing NLP solutions, model tuning, deployment of machine learning models, and familiarity with deploying in cloud environments is highly desired.,

You will be working as a C14 (People Manager) in the Citi Analytics & Information Management (AIM) team based in Pune, India. Reporting to the Director/Managing Director, AIM, you will lead a team of 15+ data scientists in the Financial Crimes & Fraud Prevention Analytics modelling team. Your primary responsibility will be to develop and implement Machine Learning (ML) /AI/Gen AI models to mitigate fraud losses and minimize customer impact. As the team lead, you will be expected to work as a Subject Matter Expert (SME) in ML/Generative AI, articulate complex AI and ML concepts to various stakeholders, and stay updated with the latest advancements in the AI and ML space. You will also provide technical leadership, mentorship, and guidance to the team to ensure successful development and implementation of ML /AI/Gen AI models. Your role will involve designing, developing, and implementing ML/AI/Gen AI solutions, as well as establishing governance frameworks for model development, deployment, and monitoring. You will need to have a strong understanding of regulatory frameworks related to model governance and risk management. To be successful in this role, you should have a minimum of 18+ years of analytics experience in core model development using ML/AI/Gen AI techniques. Strong coding skills and knowledge of Bigdata environments, as well as experience with ML / DL applications, are essential. A Bachelors degree in finance/engineering/quantitative fields (Statistics, Mathematics)/MBA is required, with a Masters degree preferred. Additionally, you should have at least 8 years of people management experience, with a track record of setting high performance standards and mentoring team members. Excellent communication skills, project management abilities, and strategic thinking are crucial for this role. You should be able to influence business outcomes and drive innovative solutions while effectively managing stakeholder relationships. Overall, this role requires a candidate with strong analytical, technical, and statistical skills, who can lead a team of data scientists to deliver projects in a fast-paced environment. If you are someone who thrives on challenges, has a passion for analytics problem solving, and can effectively communicate with both technical and non-technical stakeholders, you would be a great fit for this position.,

As a Business Analytics Analyst 2 at Citi, you will be part of the Model governance area of the North America Consumer Bank team. Your main responsibility will be to ensure comprehensive and regulatory-compliant documentation of financial models used in the bank. This role requires a balance of technical understanding, knowledge of regulatory procedures/policies, and strong documentation skills. You will report to the AVP / VP leading the team. The Next Gen Analytics (NGA) team, a part of the Analytics & Information Management (AIM) unit, focuses on model governance. Your role expectations include being detail-oriented, collaborating effectively with various stakeholders, having a statistical mindset, possessing strong communication skills, showing a sense of ownership, and continuously enhancing processes for efficiency and consistency across teams. Your responsibilities will involve working on model governance related tasks for multiple portfolios, creating and maintaining detailed documentation of model monitoring & review outcomes, ensuring compliance with Citi standards, overseeing the model inventory, working with large and complex datasets, and collaborating with other teams for model risk management and fair lending compliance. To excel in this role, you should have a good knowledge of processes, procedures, and systems related to model governance, experience in data analytics, technical skills in PySpark/Python/R/SAS programming, understanding of model risk regulations and fair lending laws, statistical analysis proficiency, project management skills, and the ability to work with multiple stakeholders. If you are a bright and talented individual with a Bachelor's Degree and at least 3 years of experience in data analytics, or a Master's Degree with 2 years of experience, or a PhD, Citi offers amazing opportunities for you. Preferred qualifications include experience in Credit Cards and Retail Banking, a background in economics/statistics/mathematics/information technology/engineering, and competencies in communication, problem-solving, teamwork, and risk awareness. This is a full-time position in the Credit Cards, Retail Banking, Financial Services, and Banking industry. If you are a person with a disability requiring accommodation, please review Accessibility at Citi. For more details, you can also refer to Citis EEO Policy Statement and the Know Your Rights poster.,

The Financial Crimes & Fraud Prevention Analytics team at Citi is looking for a skilled individual to join as a C14 (people manager) reporting to the Director/Managing Director, AIM. This role will involve leading a team of data scientists based in Pune/Bangalore, focusing on the development and implementation of Machine Learning (ML) /AI/Gen AI models for Fraud Prevention. The successful candidate will be responsible for designing, developing, and deploying generative AI based solutions, analyzing data to understand fraud patterns, and developing models to achieve overall business goals. Additionally, the individual will collaborate with the model implementation team, ensure model documentation, and address questions from model risk management (MRM) while adapting to changing business needs. Key Responsibilities: - Lead as Subject Matter Expert (SME) in the area of ML/AI/Gen AI, demonstrating strong AI and ML concepts and the ability to articulate complex concepts to diverse audiences. - Lead a team of data scientists in the development and implementation of ML /AI/Gen AI models, providing technical leadership, mentorship, and ensuring 100% execution accuracy. - Customize and fine-tune existing RAG frameworks or design new frameworks to meet project requirements. - Establish governance frameworks for model development, deployment, and monitoring to meet MRM and Fair Lending guidelines. - Oversee the end-to-end model development lifecycle and ensure timely deployment with high quality and no errors. - Manage a team of 15+ data scientists, providing career development, conflict management, performance management, coaching, mentorship, and technical guidance. Requirements: - Minimum 15+ years of analytics experience in core model development using ML/AI/Gen AI techniques. - Strong knowledge of current state-of-the-art ML/AI/Gen AI algorithms and their pros and cons. - Experience in Bigdata environments, Python, SQL, and Big Data. - Bachelors or masters degree in computer science, Data Science, Machine Learning, or a related field. Ph.D. is a plus. - At least 8 years of people management experience. - Proven track record of building and deploying generative models-based solutions in production environments. - Excellent verbal and written communication skills, with the ability to influence business outcomes and decisions. - Strong project management skills and the ability to define business requirements and create robust technical documentation. - Strategic thinking and the ability to frame business problems, with excellent analytical and statistical skills. If you are a person with a disability and need a reasonable accommodation to use Citi's search tools and/or apply for a career opportunity, please review Accessibility at Citi. For more information on Citi's EEO Policy Statement and the Know Your Rights poster, visit the Citi website.,

As a C14 (People Manager) at Citi within the Financial Crimes & Fraud Prevention Analytics Model Development team based in Pune, India, you will be reporting to the Director/Managing Director, AIM. The Citi Analytics & Information Management (AIM) team is a global community focused on connecting and analyzing information to generate actionable intelligence for business leaders. Your role will involve leading a team of 15+ data scientists, working on developing and implementing Machine Learning (ML) / AI / Gen AI models across different platforms to mitigate fraud losses, analyze transaction data, and minimize customer impact. You will collaborate with the model implementation team, ensure model documentation, and address questions from model risk management (MRM) while adapting to changing business needs. Your responsibilities will include working as a Subject Matter Expert (SME) in the field of ML/Generative AI, understanding AI and ML concepts, and articulating complex concepts to diverse audiences. You will lead the team of data scientists in developing and implementing ML / AI / Gen AI models, providing technical leadership, mentorship, and ensuring execution accuracy. Your role will also involve thought leadership in designing and implementing ML/AI/Gen AI solutions, staying updated on advancements in the field, and communicating analytical concepts effectively to technical and non-technical audiences. With a minimum of 18+ years of analytics experience, you are expected to have a strong understanding of ML/AI/Gen AI techniques, model development stages, and industry best practices. Proficiency in coding, knowledge of Bigdata environments, and experience with ML/DL applications are essential. Your educational background should include a Bachelor's degree in finance/engineering/quantitative fields (Statistics, Mathematics)/MBA, with a preference for a Master's degree. People management experience of at least 8 years is required to lead a team of data scientists, manage their career progression, and provide mentorship and technical guidance. In this role, you will establish governance frameworks for model development, deployment, and monitoring, ensuring compliance with MRM and Fair Lending guidelines. Your strategic thinking, project management skills, and ability to influence business outcomes will be crucial in driving innovative solutions and stakeholder management. Excellent communication skills, both verbal and written, are essential for seamless collaboration across teams and stakeholders. This job description offers an overview of the responsibilities and requirements for the role of C14 (People Manager) at Citi. Additional duties may be assigned as needed.,

As a part of the Citi Analytics & Information Management (AIM) team in the Financial Crimes & Fraud Prevention Analytics unit within the Fraud Operation team, you will have the opportunity to lead a team of data scientists in Pune/Bangalore. Reporting to the Director/Managing Director, AIM, your primary focus will be to develop and implement Machine Learning (ML)/AI/Gen AI models for fraud prevention. You will analyze data, identify fraud patterns, and work towards achieving overall business goals. Additionally, you will collaborate with the model implementation team, ensure model documentation, and address questions from model risk management (MRM) while adapting to changing business needs. Your role as a subject matter expert (SME) in ML/AI/Gen AI will require a strong understanding of AI and ML concepts to guide your team effectively. You will lead a team of data scientists in developing and implementing ML/AI/Gen AI models on various platforms, providing technical leadership and ensuring 100% execution accuracy. Your expertise in customizing and fine-tuning RAG frameworks, designing new frameworks, and implementing state-of-the-art ML/AI/Gen AI algorithms will be crucial in meeting and exceeding project requirements. To excel in this role, you must possess a minimum of 15+ years of analytics experience in core model development using ML/AI/Gen AI techniques. A strong knowledge of model development stages, industry best practices, and the ability to recommend appropriate algorithms for business solutions are essential. Your proficiency in coding, Bigdata environments, and various ML/DL applications will be instrumental in delivering projects successfully. Additionally, you should have experience in model execution and governance in any domain. As a people manager overseeing a team of 15+ data scientists, some of whom may be managers themselves, your responsibilities will include managing their career progression, conflict resolution, performance management, coaching, mentorship, and technical guidance. You will be expected to set high performance standards, provide mentorship, and retain talent while effectively managing attrition and career mobility. Your ability to communicate complex analytical concepts to both technical and non-technical audiences, influence business outcomes, and drive innovative solutions will be critical in this role. With excellent project management skills, strategic thinking abilities, and a proactive approach to risk mitigation, you will play a key role in leading the fraud operation function within AIM Financial Crimes and Fraud Prevention Analytics. If you are passionate about leveraging AI and ML technologies to combat financial crimes and fraud, and possess the requisite experience and skills outlined above, we encourage you to apply for this challenging and rewarding opportunity at Citi.,

Citi's mission is to serve as a trusted partner to clients by responsibly providing financial services that enable growth and economic progress. With over 200 years of experience, Citi helps clients meet challenges and seize opportunities. Analytics and Information Management (AIM) at Citi was established in 2003 and is located in multiple cities in India including Bengaluru, Chennai, Pune, and Mumbai. The AIM community connects and analyzes information to create actionable intelligence for business leaders, identifying revenue growth opportunities in partnership with businesses through analytic methodologies. The North America Consumer Bank Data Science and Modeling team uses big data tools and machine learning techniques to analyze millions of prospects and billions of customer transactions. The team extracts insights, identifies opportunities, builds predictive models, and designs strategies for various business problems. The Business Analytics Analyst 1 role within the Model governance area of the North America Consumer Bank team is responsible for ensuring comprehensive and regulatory-compliant documentation of financial models used in the bank. The Next Gen Analytics (NGA) team, a part of the AIM unit, focuses on detailed model governance work. The role requires attention to detail, effective collaboration with various stakeholders, a statistical mindset, strong communication skills, a sense of ownership for project delivery, and continuous process enhancement for efficiency and consistency. The Business Analytics Analyst 1 is responsible for creating, updating, and maintaining detailed documentation related to model monitoring and review processes, ensuring compliance with Citi standards and providing guidance on governance best practices. The role involves overseeing model inventory, working with large and complex data sets using tools like Python, PySpark, SQL, SAS, and R, collaborating with other teams within the organization, and ensuring quality control over deliverables. Candidates should have a Bachelor's or Master's degree in a relevant field, 1-3 years of experience in data analytics, technical skills in programming and data analysis, familiarity with model risk management and fair lending laws, and the ability to handle multiple projects simultaneously. Key requirements include hands-on experience in data analytics tools, understanding of model risk regulations, proficiency in statistical analysis and modeling techniques, capability to maintain models in production, strong communication and project management skills, and a detail-oriented and self-motivated approach. Experience in Credit Cards and Retail Banking is preferred. A Bachelor's or Master's degree in Economics, Statistics, Mathematics, Information Technology, Computer Applications, or Engineering from a reputable institute is required. The role is full-time in the Credit Cards, Retail Banking, Financial Services, Banking industry.,

We are looking for a highly skilled MLOps Engineer to design, deploy, and manage machine learning pipelines in Google Cloud Platform (GCP). Your responsibilities will include automating ML workflows, optimizing model deployment, ensuring model reliability, and implementing CI/CD pipelines for ML systems. You will collaborate with technical teams to develop cutting-edge machine learning systems that drive business value. In this role, you will manage the deployment and maintenance of machine learning models in production environments, ensuring seamless integration with existing systems. You will monitor model performance using metrics such as accuracy, precision, recall, and F1 score, addressing issues like performance degradation, drift, or bias. Troubleshooting problems, maintaining documentation, and managing model versions for audit and rollback will be part of your routine tasks. Your duties will also involve analyzing monitoring data proactively to identify potential issues and providing regular performance reports to stakeholders. Additionally, you will focus on optimizing queries and pipelines, as well as modernizing applications when necessary. To qualify for this role, you should have expertise in programming languages like Python and SQL, along with a solid understanding of best MLOps practices for deploying enterprise-level ML systems. Familiarity with Machine Learning concepts, models, and algorithms, such as regression, clustering, and neural networks, including deep learning and transformers, is essential. Experience with GCP tools like BigQueryML, Vertex AI Pipelines, Model Versioning & Registry, Cloud Monitoring, and Kubernetes is preferred. Strong communication skills, both written and oral, are crucial, as you will be required to prepare detailed technical documentation for new and existing applications. You should demonstrate strong ownership and collaborative qualities in your domain, taking the initiative to identify and drive opportunities for improvement and process streamlining. A Bachelor's Degree in a quantitative field or equivalent job experience is required for this position. Experience in Azure MLOPS, familiarity with Cloud Billing, setting up or supporting NLP, Gen AI, LLM applications with MLOps features, and working in an Agile environment are considered bonus qualifications. If you are passionate about MLOps, have a knack for problem-solving, and enjoy working in a collaborative environment to deliver innovative machine learning solutions, we would like to hear from you.,

As a Model Monitoring/Model Validation professional, you will be responsible for monitoring, validating, implementing, and maintaining regulatory models in the credit risk domain. Your role will involve helping with various aspects of model validation, performing necessary tests like model performance, sensitivity, and back-testing, and collaborating with the model governance team on model build and monitoring. You will work closely with cross-functional teams, including business stakeholders, model validation, and governance teams, to ensure the delivery of high-quality client services, including model documentations, within expected timeframes. To excel in this role, you should have a minimum of 2+ years of experience in executing end-to-end monitoring, validation, production, and implementation of risk model validation and monitoring. You should also possess an understanding of marketing and general analytics problems, and be able to manage assigned projects efficiently, ensuring accuracy and timely delivery of deliverables. Additionally, you will be responsible for training, coaching, and developing team members to enhance their skills and performance. The ideal candidate for this position should hold previous experience (2+ years) in analytics, preferably in the BFSI sector. You should have a good grasp of General Analytics and Fraud Analytics, along with a track record of problem-solving roles and involvement in strategic initiatives. Strong problem-solving skills will be essential to succeed in this role and contribute effectively to the model monitoring and validation processes.,

As a Business Analytics Analyst 1 within the Model governance area of the North America Consumer Bank team at Citi, you will be responsible for ensuring comprehensive and regulatory-compliant documentation of financial models used in the North America Consumer Bank. This role requires a balance of technical understanding, regulatory procedures/policies, and strong documentation skills. You will report to the AVP / VP leading the team. The Next Gen Analytics (NGA) team, a part of the Analytics & Information Management (AIM) unit, focuses on various areas of work including detail-oriented tasks, effective collaboration, statistical mindset, communication skills, strong ownership, process enhancement, project management, coaching, and mentoring. As the Business Analytics Analyst 1, you will work on model governance related responsibilities for multiple portfolios, creating, updating, and maintaining detailed documentation of outcomes from model monitoring & review processes, ensuring compliance with Citi standards and providing guidance on governance best practices. Your role will involve overseeing the model inventory, ensuring proper documentation, validation, and approval processes are followed, and compliance with policies, procedures, and relevant deadlines associated with validation, ongoing monitoring, and model change processes. Working with large and complex data sets using tools such as Python, PySpark, SQL, SAS, and R will be part of your responsibilities, along with collaborating with other team members, peers, and stakeholders. You will be expected to demonstrate attention to detail, strong analytical and process management skills, and assess risk when making business decisions, while maintaining compliance with applicable laws, rules, and regulations. Your role will also require clear and concise communication, both written and verbal, strong project management skills, attention to detail, and the ability to handle multiple projects simultaneously. If you are a bright and talented individual with a Bachelor's Degree and 1-3 years of experience in data analytics, or a Master's Degree with 0-2 years of experience in data analytics, or a PhD, Citi offers amazing opportunities for you. Technical skills, experience in model risk management, model validation/monitoring/reporting, understanding of model risk regulations and fair lending laws, and proficiency in Statistical Analysis with exposure to Machine Learning & Deep learning modeling techniques are desired qualities. Self-motivation, detail orientation, and experience in Credit Cards and Retail Banking are preferred. Citi values competencies such as strong communication skills, stakeholder management, analytical and problem-solving skills, team player mindset, control orientation, risk awareness, experience in a quantitative field, willingness to learn, can-do attitude, and ability to build partnerships with cross-functional leaders. A Bachelor's/Master's degree in Economics, Statistics, Mathematics, Information Technology, Computer Applications, Engineering, or related fields from a premier institute is required for this role. This is a full-time employment opportunity in the Credit Cards, Retail Banking, Financial Services, Banking industry at Citi. If you are a person with a disability and need a reasonable accommodation to use the search tools or apply for a career opportunity, review Accessibility at Citi. View Citis EEO Policy Statement and the Know Your Rights poster for more information.,

The team at Walmart Global Tech builds reusable technologies to assist in acquiring customers, onboarding and empowering merchants, and ensuring a seamless experience for all stakeholders. They focus on optimizing tariffs and assortment while maintaining Walmart's philosophy of Everyday Low Cost. Additionally, the team creates personalized omnichannel experiences for customers across various platforms. The Marketplace team serves as the gateway for Third-Party sellers, enabling them to manage their onboarding, catalog, orders, and returns. They are responsible for designing, developing, and operating large-scale distributed systems using cutting-edge technologies. As a Staff Data Scientist at Walmart Global Tech, you will be responsible for developing scalable end-to-end data science solutions for data products. You will collaborate with data engineers and analysts to build ML- and statistics-driven data quality workflows. Your role will involve solving business problems by scaling advanced Machine Learning algorithms on large datasets. You will own the MLOps lifecycle, from data monitoring to model lifecycle management. Additionally, you will demonstrate thought leadership by consulting with product and business stakeholders to deploy machine learning solutions. The ideal candidate should have knowledge of machine learning and statistics, experience with web service standards, and proficiency in architecting solutions with Continuous Integration and Continuous Delivery. Strong coding skills in Python, experience with Big Data technologies like Hadoop and Spark, and the ability to work in a big data ecosystem are preferred. Candidates should have experience in developing and deploying machine learning solutions and collaborating with data scientists. Effective communication skills and the ability to present complex ideas clearly are also desired. Educational qualifications in Computer Science, Statistics, Engineering, or related fields are preferred. Candidates with prior experience in Delivery Promise Optimization or Supply Chain domains and hands-on experience in Spark or similar frameworks will be given preference. At Walmart Global Tech, you will have the opportunity to work in a dynamic environment where your contributions can impact millions of people. The team values innovation, collaboration, and continuous learning. Join us in reimagining the future of retail and making a difference on a global scale. Walmart Global Tech offers a hybrid work model that combines in-office and virtual presence. The company provides competitive compensation, incentive awards, and a range of benefits including maternity leave, health benefits, and more. Walmart fosters a culture of belonging where every associate is valued and respected. The company is committed to creating opportunities for all associates, customers, and suppliers. As an Equal Opportunity Employer, Walmart believes in understanding, respecting, and valuing the uniqueness of individuals while promoting inclusivity.,

In this role, you will: Establish, implement and maintain risk standards and programs to drive compliance with federal, state, agency, legal and regulatory and Corporate Policy requirements Oversee the Front Line's execution and challenges appropriately on compliance related decisions Provide oversight and monitoring of risk-based compliance programs Develop and oversee standards Provide subject matter expertise with comprehensive knowledge of business and functional area Provide compliance risk expertise and consulting for projects and initiatives with moderate risk for a business line or functional area Monitor reporting, escalation, and timely remediation of issues, deficiencies or regulatory matters regarding compliance risk management Provide direction to the business on developing corrective action plans and effectively managing regulatory change Provide compliance risk expertise Consult for projects and initiatives with moderate risk for a business line Identify and recommend opportunities for process improvement and risk control development Provide direction to the business on developing corrective action plans and effectively managing regulatory change Report findings and make recommendations to management appropriate committees Interpret policies, procedures, and compliance requirements Collaborate and consult with peers, colleagues and managers to resolve issues and achieve goals Work with complex business units, rules and regulations on moderate risk compliance matters Receive direction from leaders and exercise independent judgment while developing the knowledge to understand function, policies, procedures, and compliance requirements Required Qualifications: 4+ years of Compliance experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Model Validation or Governance Background Working knowledge of Data / Privacy laws and Fair Credit Reporting Act (FCRA) requirements Job Expectations: Provide governance over in-scope consumer facing Models, which includes the review of the model to determine if there are FCRA or Data Concerns Solicit feedback from Legal, Business Aligned Compliance Officers and Horizontal Compliance functions during the review of Models Prepare and archive model review documentation Review initial Model Classification, Risk Rank and Risk Rank Overrides and Risk Rank Changes Review and Challenge Model Validation Results Participate in Model Monitoring Programs and any Required Quarterly/Annual Monitoring Reviews

You are a highly skilled and motivated Lead Data Scientist / Machine Learning Engineer sought to join a team pivotal in the development of a cutting-edge reporting platform. This platform is designed to measure and optimize online marketing campaigns effectively. Your role will involve focusing on data engineering, ML model lifecycle, and cloud-native technologies. You will be responsible for designing, building, and maintaining scalable ELT pipelines, ensuring high data quality, integrity, and governance. Additionally, you will develop and validate predictive and prescriptive ML models to enhance marketing campaign measurement and optimization. Experimenting with different algorithms and leveraging various models will be crucial in driving insights and recommendations. Furthermore, you will deploy and monitor ML models in production and implement CI/CD pipelines for seamless updates and retraining. You will work closely with data analysts, marketing teams, and software engineers to align ML and data solutions with business objectives. Translating complex model insights into actionable business recommendations and presenting findings to stakeholders will also be part of your responsibilities. Qualifications & Skills: Educational Qualifications: - Bachelors or Masters degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, or related field. - Certifications in Google Cloud (Professional Data Engineer, ML Engineer) is a plus. Must-Have Skills: - Experience: 5-10 years with the mentioned skillset & relevant hands-on experience. - Data Engineering: Experience with ETL/ELT pipelines, data ingestion, transformation, and orchestration (Airflow, Dataflow, Composer). - ML Model Development: Strong grasp of statistical modeling, supervised/unsupervised learning, time-series forecasting, and NLP. - Programming: Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL for large-scale data processing. - Cloud & Infrastructure: Expertise in GCP (BigQuery, Vertex AI, Dataflow, Pub/Sub, Cloud Storage) or equivalent cloud platforms. - MLOps & Deployment: Hands-on experience with CI/CD pipelines, model monitoring, and version control (MLflow, Kubeflow, Vertex AI, or similar tools). - Data Warehousing & Real-time Processing: Strong knowledge of modern data platforms for batch and streaming data processing. Nice-to-Have Skills: - Experience with Graph ML, reinforcement learning, or causal inference modeling. - Working knowledge of BI tools (Looker, Tableau, Power BI) for integrating ML insights into dashboards. - Familiarity with marketing analytics, attribution modeling, and A/B testing methodologies. - Experience with distributed computing frameworks (Spark, Dask, Ray). Location: - Bengaluru Brand: - Merkle Time Type: - Full time Contract Type: - Permanent,

As an experienced AI Architect, you will be responsible for leading the development of AI and Machine Learning infrastructure and specialized language models for HR applications. Your role will involve establishing and leading MLOps practices and driving the creation of scalable, production-ready AI/ML systems. You will collaborate with business teams to discuss the feasibility of AI/ML use cases and translate the vision of business leaders into realistic technical implementations. Your expertise will be crucial in defining the AI architecture, selecting appropriate technologies, designing and implementing robust ML infrastructure and deployment pipelines, and establishing comprehensive MLOps practices for model training, versioning, and deployment. In this role, you will lead the development of HR-specialized language models (SLMs), implement model monitoring, observability, and performance optimization frameworks, and develop fine-tuning strategies for large language models. You will create and maintain data quality assessment and validation processes, design model versioning systems and A/B testing frameworks, and define technical standards and best practices for AI development while optimizing infrastructure for cost, performance, and scalability. To be successful in this position, you should have 7+ years of experience in ML/AI engineering or related technical roles, with at least 3 years of hands-on experience in MLOps and production ML systems. Your expertise should include fine-tuning and adapting foundation models, knowledge of model serving infrastructure and orchestration, proficiency with MLOps tools such as MLflow, Kubeflow, Weights & Biases, and experience in implementing model versioning and A/B testing frameworks. Proficiency in Python and ML frameworks like PyTorch, TensorFlow, Hugging Face, as well as experience with cloud-based ML platforms such as AWS, Azure, Google Cloud, are essential. A proven track record of deploying ML models at scale, developing AI applications for enterprise software domains, and knowledge of distributed training techniques and infrastructure will be beneficial. Familiarity with retrieval-augmented generation (RAG) systems, vector databases like Pinecone, Weaviate, Milvus, and understanding of responsible AI practices and bias mitigation are also desired. A Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field is required for this position.,

As an experienced machine learning professional with expertise in deep learning and statistical modeling for earth observation data applications, your key responsibilities will include developing models for segmentation, object classification, crop monitoring, and disaster management. It is essential for you to have proficiency in Python, ML frameworks such as TensorFlow and PyTorch, and strong research skills. An advanced degree is required for this role. SatSure is a deep tech, decision intelligence company that focuses on agriculture, infrastructure, and climate action in the developing world. The company aims to make insights from earth observation data accessible to all. Joining SatSure means being at the forefront of building a deep tech company from India that aims to solve global problems. In this role, you will be responsible for implementing deep-learning models and frameworks for various applications in agriculture and infrastructure using earth observation data. You will design and implement performance evaluation frameworks, explore new methods for improving performance, and build model monitoring and active learning pipelines. Additionally, you will work on solving research problems related to land use and land cover (LULC), crop classification, change monitoring, and disaster management using earth observations. To qualify for this role, you should have a master's degree or PhD in Engineering, Statistics, Mathematics, or Computer Science with 5-8 years of experience in machine learning-based data product research and development. Proficiency in tools and frameworks related to computer science, probability, statistics, learning theory, and deep learning fundamentals is required. Experience with statistical modeling techniques and deep learning models like CNN, RNN, Transformers, and GANs is necessary. You should also be proficient in Python and have hands-on experience in using ML frameworks such as TensorFlow, PyTorch, PyTorch Lightning, and MxNet. Additional qualifications include the ability to design, develop, and optimize machine learning/deep learning models, knowledge of applying ML to earth observation data, and an appetite for research and implementing innovative solutions for complex problems. In addition to a challenging and rewarding work environment, SatSure offers benefits such as medical health cover for you and your family, access to mental health experts, dedicated allowances for learning and skill development, and a comprehensive leave policy. The interview process includes an introductory call, assessment, presentation, multiple interview rounds, and a culture/HR round. Join SatSure to be a part of a dynamic team that is making a positive impact on the world through innovative technology and deep learning solutions.,

We are looking for a skilled Data Engineer to join our team, working on end-to-end data engineering and data science use cases. The ideal candidate will have strong expertise in Python or Scala, Spark (Databricks), and SQL, building scalable and efficient data pipelines on Azure. Responsibilities include designing, building, and maintaining scalable ETL/ELT data pipelines using Azure Data Factory, Databricks, and Spark. Developing and optimizing data workflows using SQL and Python or Scala for large-scale data processing and transformation. Implementing performance tuning and optimization strategies for data pipelines and Spark jobs to ensure efficient data handling. Collaborating with data engineers to support feature engineering, model deployment, and end-to-end data engineering workflows. Ensuring data quality and integrity by implementing validation, error-handling, and monitoring mechanisms. Working with structured and unstructured data using technologies such as Delta Lake and Parquet within a Big Data ecosystem. Contributing to MLOps practices, including integrating ML pipelines, managing model versioning, and supporting CI/CD processes. Primary Skills required are Data Engineering & Cloud proficiency in Azure Data Platform (Data Factory, Databricks), strong skills in SQL and either Python or Scala for data manipulation, experience with ETL/ELT pipelines and data transformations, familiarity with Big Data technologies (Spark, Delta Lake, Parquet), expertise in data pipeline optimization and performance tuning, experience in feature engineering and model deployment, strong troubleshooting and problem-solving skills, experience with data quality checks and validation. Nice-to-Have Skills include exposure to NLP, time-series forecasting, and anomaly detection, familiarity with data governance frameworks and compliance practices, basics of AI/ML like ML & MLOps Integration, experience supporting ML pipelines with efficient data workflows, knowledge of MLOps practices (CI/CD, model monitoring, versioning). At Tesco, we are committed to providing the best for our colleagues. Total Rewards offered at Tesco are determined by four principles - simple, fair, competitive, and sustainable. Colleagues are entitled to 30 days of leave (18 days of Earned Leave, 12 days of Casual/Sick Leave) and 10 national and festival holidays. Tesco promotes programs supporting health and wellness, including insurance for colleagues and their family, mental health support, financial coaching, and physical wellbeing facilities on campus. Tesco in Bengaluru is a multi-disciplinary team serving customers, communities, and the planet. The goal is to create a sustainable competitive advantage for Tesco by standardizing processes, delivering cost savings, enabling agility through technological solutions, and empowering colleagues. Tesco Technology team consists of over 5,000 experts spread across the UK, Poland, Hungary, the Czech Republic, and India, dedicated to various roles including Engineering, Product, Programme, Service Desk and Operations, Systems Engineering, Security & Capability, Data Science, and others.,

You will be joining EXL, a leading operations management and analytics company dedicated to helping businesses thrive in competitive and disruptive environments. Through our innovative methodologies encompassing advanced analytics, data management, digital solutions, BPO, consulting, industry best practices, and cutting-edge technology platforms, we delve deep to support companies in enhancing global operations, fostering data-driven insights, improving customer satisfaction, and effectively managing risk and compliance. EXL caters to various industries such as insurance, healthcare, banking and financial services, utilities, travel, transportation, and logistics, with a team of over 30,000 professionals located across the United States, Europe, Asia (mainly India and the Philippines), Latin America, Australia, and South Africa. In the realm of EXL Analytics, we provide actionable solutions to business challenges through statistical data mining, advanced analytics techniques, and a consultative approach. By utilizing our proprietary methodology and top-tier technology, EXL Analytics adopts an industry-specific strategy to revolutionize clients" decision-making processes and embed analytics deeply into their business operations. Our team of nearly 2,000 data scientists and analysts worldwide support client organizations in diverse areas such as risk minimization, advanced marketing strategies, pricing and CRM techniques, internal cost analysis, and optimizing resources within the organization. EXL Analytics caters to industries like insurance, healthcare, banking, capital markets, utilities, retail and e-commerce, travel, transportation, and logistics. Your role will involve being a proficient credit risk model professional with expertise in model monitoring, validation, implementation, and maintenance of regulatory models. Some of your key responsibilities will include assisting in various aspects of model risk management in alignment with regulations, conducting essential tests such as model performance evaluations, sensitivity analyses, and back-testing, collaborating with the model governance team on model development and monitoring, liaising with cross-functional teams including business stakeholders, model validation, and governance teams, delivering high-quality client services encompassing model documentation within stipulated timeframes. To excel in this role, you should have a minimum of 2+ years of experience in executing end-to-end monitoring, validation, production, and implementation of credit risk models, particularly CCAR/CECL/IFRS9 regulatory models. You should possess a strong comprehension of credit risk regulatory models, along with expertise in marketing and general analytics problems. Your ability to manage assigned projects efficiently, ensuring accuracy and timely deliverables, as well as training, coaching, and developing team members, will be crucial for success. For qualifications, you should have prior analytics experience (2+ years), preferably in the BFSI sector, with a good understanding of General Analytics and Fraud Analytics. Past experience in roles involving problem-solving and strategic initiatives is advantageous. Proficiency in SAS/SAS macros, Python, or SQL is essential, while hands-on experience in R or any other analytical software would be a plus. Strong problem-solving skills will further enhance your suitability for this role.,

As an MLOps Engineer at our Bangalore location, you will play a pivotal role in designing, developing, and maintaining robust MLOps pipelines for generative AI models on AWS. With a Bachelor's or Master's degree in Computer Science, Data Science, or a related field, you should have at least 2 years of proven experience in building and managing MLOps pipelines, preferably in a cloud environment like AWS. Your responsibilities will include implementing CI/CD pipelines to automate model training, testing, and deployment workflows. You should have a strong grasp of containerization technologies such as Docker, container orchestration platforms, and AWS services like SageMaker, Bedrock, EC2, S3, Lambda, and CloudWatch. Practical knowledge of CI/CD principles and tools, along with experience working with large language models, will be essential for success in this role. Additionally, your role will involve driving technical discussions, explaining options to both technical and non-technical audiences, and ensuring software product cost monitoring and optimization. Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow, familiarity with generative AI models, and experience with infrastructure-as-code tools like Terraform or CloudFormation will be advantageous. Moreover, knowledge of model monitoring and explainability techniques, various data storage and processing technologies, and experience with other cloud platforms like GCP will further enhance your capabilities. Any contributions to open-source projects related to MLOps or machine learning will be a valuable asset. At CGI, we believe in ownership, teamwork, respect, and belonging. Your work as an MLOps Engineer will focus on turning meaningful insights into action, with opportunities to develop innovative solutions, build relationships with teammates and clients, and access global capabilities to scale your ideas. Join us in shaping your career at one of the largest IT and business consulting services firms globally.,

Job Responsibilities: Data Collection and Preparation: Collaborate with cross-functional teams, including domain experts, to collect and preprocess relevant data from multiple sources (e.g., healthcare records, financial transactions). Conduct thorough data analysis, cleaning, and feature engineering to transform raw data into usable formats for model development. Ensure data privacy and security compliance when handling sensitive data. Machine Learning Model Development: Design, build, and implement machine learning models tailored to solve specific business challenges Select appropriate datasets and data representation methods for various projects (e.g., time-series data, structured/unstructured data). Experiment with and optimize algorithms (e.g., supervised learning, unsupervised learning, anomaly detection) to improve model accuracy and efficiency. Perform statistical analysis, test different hypotheses, and fine-tune models using test results. Model Optimization and Evaluation: Evaluate model performance using various metrics (accuracy, precision, recall, F1 score, etc.) and apply techniques such as cross-validation, hyperparameter tuning Continuously improve models based on feedback, new data, and evolving business requirements. Ensure models can scale effectively in production environments. Model Deployment and Monitoring: Deploy machine learning models into production using cloud services (AWS, GCP, Azure) or containerized environments (Docker, Kubernetes). Oversee and monitor the performance of models in real-time, ensuring they provide accurate and actionable insights. Implement model retraining and continuous learning processes to maintain performance over time. Research and Innovation: Stay current with the latest developments in machine learning, AI, and relevant technologies by actively researching and experimenting with new algorithms, models, and techniques. Propose and integrate novel approaches into existing workflows to improve model accuracy, efficiency, and scalability. Required Qualifications: Technical Skills: Programming Languages : Proficiency in Python, Java, or R, with strong expertise in Python for machine learning tasks. Machine Learning Frameworks : Familiarity with TensorFlow, PyTorch, Keras, and scikit-learn for developing and optimizing models. Mathematics & Statistics : Strong foundation in linear algebra, calculus, probability, and statistics to understand and apply machine learning algorithms effectively. Big Data Technologies : Experience working with tools like Hadoop, Apache Spark for handling large datasets. Cloud Computing : Hands-on experience with cloud platforms such as AWS, GCP, or Azure for deploying and maintaining machine learning models. Version Control & Deployment : Proficient with version control tools like Git and experience in CI/CD pipelines for model deployment. Domain-Specific Knowledge (Desired): Healthcare/Medical Data : Understanding of medical datasets (e.g., patient records, diagnostic imaging) and how to build models for healthcare applications (e.g., predicting neurological disorders). Financial Data/Fraud Detection : Experience with financial transaction data and building systems for detecting fraudulent activity and financial anomalies (e.g., Anti-Money Laundering models). Soft Skills: Problem-Solving : Strong analytical and problem-solving skills, with the ability to approach challenges in creative and innovative ways. Communication : Excellent written and verbal communication skills, with the ability to explain complex machine learning concepts to non-technical stakeholders. Team Collaboration : Ability to work collaboratively in an interdisciplinary team, sharing knowledge and working towards common goals.

As a part of Barclays Analyst Impairment team, you will play a crucial role in embedding control functionality by leading the development of the team's output. Your responsibilities will include helping colleagues demonstrate analytical and technical skills, along with knowledge of retail credit risk management fundamentals, especially in impairment management. It is essential to showcase sound judgment while collaborating with the wider team and management. To excel in this role, you will need to: - Provide commentary in various forums and own IFRS9 risk models throughout their lifecycle, from data governance to monitoring. - Develop Post Model Adjustments (PMA) to address inaccuracies and underperformance in models. - Review monitoring reports to identify reasons for model underperformance and liaise with modelling teams. - Design and implement tactical and strategic remediation, as well as support the production of commentary packs for multiple forums and group impairment committee. Additionally, some highly valued skills for this role include: - Review and challenge IFRS9 impairment models, both SPOT and Forecasting. - Produce annual and monthly forecasts for IFRS9. - Maintain management information related to impairment metrics such as stock coverage. - Possess a working knowledge of key regulatory requirements for IFRS9 and apply them to existing processes and reporting. - Present results and communicate effectively with management and stakeholders. - Foster a culture of decision-making through the provision of robust and accurate analyses. Your performance in this role will be evaluated based on key critical skills relevant for success, including risk and controls, change and transformation, business acumen, strategic thinking, digital and technology, as well as job-specific technical skills. This position is based in Noida. Purpose of the role: The primary purpose of this role is to evaluate and assess the potential impairment of financial assets, ensuring accurate reflection of the bank's economic value of its assets in financial statements. Accountabilities: - Identify potential impairment triggers and assess the potential for impairment of financial assets by analyzing relevant financial and non-financial information. - Apply quantitative and qualitative impairment tests to determine asset impairment. - Calculate impairment provision, reflect impairment loss, and prepare accurate impairment disclosures for financial statements. - Manage the performance of impaired assets and reassess their impairment status regularly. Analyst Expectations: - Perform activities timely and to a high standard, consistently driving continuous improvement. - Possess in-depth technical knowledge and experience in the assigned area of expertise. - Lead and supervise a team, guide professional development, allocate work requirements, and coordinate team resources. - Demonstrate leadership behaviours for creating an environment for colleagues to thrive and deliver excellently. All colleagues are expected to embody the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship, as well as demonstrate the Barclays Mindset of Empower, Challenge, and Drive in their daily behaviors and actions.,

As a Data Scientist at our company, you will play a crucial role in supporting the development and deployment of machine learning models and analytics solutions that enhance decision-making processes throughout the mortgage lifecycle, spanning from acquisition to servicing. Your responsibilities will involve building predictive models, customer segmentation tools, and automation workflows to drive operational efficiency and improve customer outcomes. Collaborating closely with senior data scientists and cross-functional teams, you will be tasked with translating business requirements into well-defined modeling tasks, with opportunities to leverage natural language processing (NLP), statistical modeling, and experimentation frameworks within a regulated financial setting. You will report to a senior leader in Data Science. Your key responsibilities will include: - Developing and maintaining machine learning models and statistical tools for various use cases such as risk scoring, churn prediction, segmentation, and document classification. - Working collaboratively with Product, Engineering, and Analytics teams to identify data-driven opportunities and support automation initiatives. - Translating business inquiries into modeling tasks, contributing to experimental design, and defining success metrics. - Assisting in the creation and upkeep of data pipelines and model deployment workflows in collaboration with data engineering. - Applying techniques such as supervised learning, clustering, and basic NLP to structured and semi-structured mortgage data. - Supporting model monitoring, performance tracking, and documentation to ensure compliance and audit readiness. - Contributing to internal best practices, engaging in peer reviews, and participating in knowledge-sharing sessions. - Staying updated with advancements in machine learning and analytics pertinent to the mortgage and financial services sector. Qualifications: - Minimum education required: Masters or PhD in engineering, math, statistics, economics, or a related field. - Minimum years of experience required: 2 (or 1 post-PhD), preferably in mortgage, fintech, or financial services. - Required certifications: None Specific skills or abilities needed: - Experience working with structured and semi-structured data; exposure to NLP or document classification is advantageous. - Understanding of the model development lifecycle, encompassing training, validation, and deployment. - Familiarity with data privacy and compliance considerations (e.g., ECOA, CCPA, GDPR) is desirable. - Strong communication skills and the ability to present findings to both technical and non-technical audiences. - Proficiency in Python (e.g., scikit-learn, pandas), SQL, and familiarity with ML frameworks like TensorFlow or PyTorch.,

As an Analyst in Impairment at Barclays, you will play a crucial role in embedding control functionality by leading the development of outputs for the team. Your responsibilities will include supporting colleagues in demonstrating analytical and technical skills, as well as knowledge of retail credit risk management fundamentals, especially in impairment management. Collaboration with the wider team and management will require sound judgment from you. To excel in this role, you should be able to provide commentary for various forums, own IFRS9 risk models throughout their lifecycle, develop Post Model Adjustments, review model monitoring reports, design and implement remediation strategies, and support the production of commentary packs and decks for multiple forums and committees. Some other key skills that are highly valued for this role include reviewing and challenging IFRS9 impairment models, producing annual and monthly forecasts, maintaining management information on impairment metrics, understanding key regulatory requirements for IFRS9, presenting results to stakeholders, and fostering a culture of decision-making through robust analyses. You may undergo an assessment based on critical skills such as risk and controls, change and transformation, business acumen, strategic thinking, digital and technology, and job-specific technical skills. This role is based in Noida. The purpose of this role is to evaluate and assess the potential impairment of financial assets to ensure accurate reflection of the bank's economic value of assets in its financial statements. Your accountabilities will include identifying potential impairment triggers, analyzing relevant information, applying impairment tests, assessing impairment loss, calculating impairment provisions, managing impaired assets" performance, and reassessing their impairment status regularly. As an Analyst, you are expected to perform activities timely and to a high standard, demonstrate in-depth technical knowledge, lead and supervise a team, guide professional development, and exhibit clear leadership behaviours. You will impact related teams, partner with other functions, manage risk, and strengthen controls. All colleagues at Barclays are expected to uphold the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship, along with demonstrating the Barclays Mindset of Empower, Challenge, and Drive to guide their behavior and actions.,

You are an experienced OCI AI Architect who will be responsible for leading the design and deployment of Gen AI, Agentic AI, and traditional AI/ML solutions on Oracle Cloud. Your role will involve a deep understanding of Oracle Cloud Architecture, Gen AI, Agentic and AI/ML frameworks, data engineering, and OCI-native services. The ideal candidate will possess a combination of deep technical expertise in AI/ML and Gen AI over OCI along with domain knowledge in Finance and Accounting. Your key responsibilities will include designing, architecting, and deploying AI/ML and Gen AI solutions on OCI using native AI services, building agentic AI solutions using frameworks such as LangGraph, CrewAI, and AutoGen, leading the development of machine learning AI/ML pipelines, and providing technical guidance on MLOps, model versioning, deployment automation, and AI governance. You will collaborate with functional SMEs, application teams, and business stakeholders to identify AI opportunities, advocate for OCI-native capabilities, and support customer presentations and solution demos. To excel in this role, you should have 10-15 years of experience in Oracle Cloud and AI, with at least 5 years of proven experience in designing, architecting, and deploying AI/ML & Gen AI solutions over OCI AI stack. Strong Python development experience, knowledge of LLMs such as Cohere and GPT, proficiency in AI/ML/Gen AI frameworks like TensorFlow, PyTorch, Hugging Face, and hands-on experience with OCI services are required. Additionally, skills in AI governance, Agentic AI frameworks, AI architecture principles, and leadership abilities are crucial for success. Qualifications for this position include Oracle Cloud certifications such as OCI Architect Professional, OCI Generative AI Professional, OCI Data Science Professional, as well as a degree in Computer Science or MCA. Any degree or diploma in AI would be preferred. Experience with front-end programming languages, Finance domain solutions, Oracle Cloud deployment, and knowledge of Analytics and Data Science would be advantageous. If you are a highly skilled and experienced OCI AI Architect with a passion for designing cutting-edge AI solutions on Oracle Cloud, we invite you to apply and join our team for this exciting opportunity.,

The Data Science Lead position at our company is a key role that requires a skilled and innovative individual to join our dynamic team. We are looking for a Data Scientist with hands-on experience in Copilot Studio, M365, Power Platform, AI Foundry, and integration services. In this role, you will collaborate closely with cross-functional teams to design, build, and deploy intelligent solutions that drive business value and facilitate digital transformation. Key Responsibilities: - Develop and deploy AI models and automation solutions using Copilot Studio and AI Foundry. - Utilize M365 tools and services to integrate data-driven solutions within the organization's digital ecosystem. - Design and implement workflows and applications using the Power Platform (Power Apps, Power Automate, Power BI). - Establish, maintain, and optimize data pipelines and integration services to ensure seamless data flow across platforms. - Engage with stakeholders to comprehend business requirements and translate them into actionable data science projects. - Communicate complex analytical insights effectively to both technical and non-technical audiences. - Continuously explore and assess new tools and technologies to enhance existing processes and solutions. Required Skills and Qualifications: - 5-12 years of overall experience. - Demonstrated expertise in Copilot Studio, M365, Power Platform, and AI Foundry. - Strong understanding of data integration services and APIs. - Proficient in data modeling, data visualization, and statistical analysis. - Experience with cloud platforms like Azure or AWS is advantageous. - Exceptional problem-solving and critical-thinking abilities. - Effective communication and collaboration skills. - Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field. Preferred Skills: - Familiarity with additional AI and machine learning frameworks. - Knowledge of agile methodologies and collaborative tools. - Certifications in Power Platform, Azure AI, or M365 are a plus. If you are a proactive and results-driven individual with a passion for data science and a desire to contribute to cutting-edge projects, we encourage you to apply for this challenging and rewarding opportunity as a Data Science Lead with our team.,

You are a highly experienced Senior Python & AI Engineer who will lead the development of innovative AI/ML solutions. Your strong background in Python programming, deep learning, machine learning, and proven leadership skills will drive the team towards delivering high-quality AI systems. You will architect solutions, define technical strategies, mentor team members, and ensure timely project deliveries. In the technical realm, you will be responsible for designing and implementing scalable AI/ML systems and backend services using Python. Your role includes overseeing the development of machine learning pipelines, APIs, and model deployment workflows. Reviewing code, establishing best practices, and maintaining technical quality across the team will be key aspects of your responsibilities. As a team leader, you will guide data scientists, ML engineers, and Python developers, providing mentorship, coaching, and conducting performance evaluations. You will facilitate agile practices such as sprint planning, daily stand-ups, and retrospectives. Collaboration with cross-functional teams, including product, QA, DevOps, and UI/UX, will be essential for timely feature deliveries. In AI/ML development, you will develop and optimize models for NLP, computer vision, or structured data analysis based on project requirements. Implementing model monitoring, drift detection, and retraining strategies will contribute to the success of AI initiatives. You will work closely with product managers to translate business needs into technical solutions and ensure the end-to-end delivery of features meeting performance and reliability standards. Your technical skills should include over 5 years of Python experience, 2+ years in AI/ML projects, a deep understanding of ML/DL concepts, and proficiency in frameworks like PyTorch, TensorFlow, and scikit-learn. Experience with deployment tools, cloud platforms, and CI/CD pipelines is required. Leadership qualities such as planning, estimation, and effective communication are also crucial, with at least 3 years of experience leading engineering or AI teams. Preferred qualifications include a Masters or PhD in relevant fields, exposure to MLOps practices, and familiarity with advanced AI technologies. Prior experience in fast-paced startup environments is a plus. In return, you will have the opportunity to spearhead cutting-edge AI initiatives, face diverse challenges, enjoy autonomy, and receive competitive compensation with performance-based incentives.,