myGwork - LGBTQ+ Business Community
Website:
mygwork.com
Job details:
This job is with Capco, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.
iOS App Developer - Vadodara
Location: Vadodara, India (Hybrid)
Experience: 5+ Years
6005120 Engineering Manager, Data Science and Machine Learning ![CDATA[ p strong em This job is with Morningstar, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. /em /strong /p divdivpspanspanAs an Engineering Manager, AI amp; ML (Data Collection), you will play a vital role in /spanspanexecuting/spanspan the company's AI and machine learning initiatives with a strong focus on data collection technologies. This position will require deep technical /spanspanexpertise/spanspan in unstructured data processing, data collection pipeline engineering, and a hands-on approach to managing and mentoring engineers. Your leadership will ensure that AI amp; ML data collection systems are developed and operationalized at the highest standards of performance, reliability, and security. You will be working closely with individual contributors, ensuring that projects align with broader business goals and AI/ML strategies./span/spanspan /span/p/divdivpspan /span/p/divdivpspanspanThis role requires deep /spanspanengagement/spanspan in the design, development, and maintenance /spanspanof AI amp; ML models, solutions, architecture, and services/spanspan. You will need to provide strong technical direction, problem-solve complex technical challenges, and ensure that the team consistently delivers high-quality, scalable solutions/spanspan./spanspan /spanspanYou will /spanspanleverage/spanspan your deep knowledge in areas such as advanced natural language processing (NLP)/spanspan, generative AI (GenAI)/spanspan and/spanspan large language models (LLMs), /spanspanML Operations (/spanspanMLOps/spanspan), data architecture, /spanspandata pipelines, and cloud-managed services/spanspan./span/spanspan /span/p/divdivpspan /span/p/divdivpspanspanYour leadership will ensure that our AI/ML systems align with/spanspan /spanspanglobal business strategies, /spanspanmaintaining/spanspan seamless integration and high-performance standard/spanspans/spanspan./spanspan /spanspanYou will oversee the end-to-end lifecycle of AI/ML data systems-from research and development to deployment and operationalization/spanspan./span/spanspan /span/p/divdivpspan /span/p/divdivpspanspanYou will /spanspanbe responsible for/spanspan mentoring team members, resolving technical challenges, and fostering a culture of innovation and collaboration/spanspan while /spanspanensuring they have the right tools, frameworks, and guidance to succeed/spanspan. This role offers a unique opportunity to drive impactful change in a fast-paced, dynamic environment, where your efforts will directly contribute to the success of our AI/ML initiatives globally/spanspan./spanspan /spanspanYour ability to collaborate with /spanspancross-departmental stakeholders/spanspan, provide leadership across locations, set /spanspanhigh standards/spanspan for the team, and hire, train, and /spanspanretain/spanspan exceptional talent is foundational to your success. You will /spanspansolicit/spanspan feedback, engage others with empathy, inspire creative thinking, and help foster a culture of belonging, teamwork, and purpose/spanspan./span/spanspan /span/p/divdivpspan /span/p/divdivpstrongspanTeam/spanspan Overview/span/strongspan /span/p/divdivpspanspanYou will lead a multidisciplinary team of engineers and data scientists responsible /spanspanfor building AI amp; ML /spanspansolutions and /spanspanservices/spanspan as part of robust /spanspandata collection pipelines /spanspanhandling /spanspanlarge volumes of unstructured data. Your team will focus on building scalable and reliable systems to process and categorize data that is essential for downstream /spanspandata collection processing./span/spanspan /span/p/divdivpspan /span/p/divdivpstrongspanOutline of Duties and Responsibilities/span/strongspan /span/p/divdivullipstrongspanAI amp; ML Data Collection Leadership/span/strongspanspan: Drive the execution of AI amp; ML initiatives related to data collection, ensuring that the team's efforts are aligned with overall business goals and strategies./span/spanspan /span/p/li/ul/div/divdivdivullipstrongspanTechnical Oversight/span/strongspanspan: Provide hands-on technical leadership in the engineering of ML models and services, focusing on unstructured data, NLP, and classifiers. Oversee and contribute to the implementation of scalable solutions that meet /spanspanhigh standards/spanspan of reliability and efficiency./span/spanspan /span/p/li/ul/divdivullipstrongspanTeam Leadership amp; Development/span/strongspanspan: Lead, mentor, and develop a high-performing team of engineers and data scientists, fostering a culture of innovation and continuous improvement. Ensure effective communication and coordination within your team and across geographically dispersed teams./span/spanspan /span/p/li/ul/divdivullipstrongspanNLP Technologies/span/strongspanspan: Contribute to the development and application of NLP techniques, including classifiers, transformers, LLMs, and other methodologies, to efficiently process and categorize unstructured data. Ensure these models are integrated seamlessly into the broader AI/ML infrastructure./span/spanspan /span/p/li/ul/divdivullipstrongspanData Pipeline Engineering/span/strongspanspan: Design, develop, and /spanspanmaintain/spanspan advanced data collection pipelines, /spanspanutilizing/spanspan orchestration, messaging, database, and data platform technologies. Ensure pipelines are /spanspanoptimized/spanspan for scalability, performance, and reliability./span/spanspan /span/p/li/ul/divdivullipstrongspanCross-functional Collaboration/span/strongspanspan: Work closely with other AI/ML teams, data collection engineering teams, product management, and others to ensure data collection efforts support broader AI/ML goals and product /spanspanobjectives/spanspan./span/spanspan /span/p/li/ul/divdivullipstrongspanInnovation amp; Continuous Improvement/span/strongspanspan: Continuously explore and implement /spanspannew technologies/spanspan and methodologies to enhance the efficiency and accuracy of data collection and processing systems. Stay at the forefront of advancements in NLP and data processing./span/spanspan /span/p/li/ul/divdivullipstrongspanSystem Integrity amp; Security/span/strongspanspan: Ensure that all data collection systems meet the highest standards of integrity, security, and compliance. Implement best practices for data governance and model transparency./span/spanspan /span/p/li/ul/divdivullipstrongspanTalent Acquisition amp; Retention/span/strongspanspan: Play an active role in recruiting, training, and /spanspanretaining/spanspan top engineering talent. Foster an environment where team members are encouraged to innovate, feel valued, and achieve their full potential./span/spanspan /span/p/li/ul/divdivullipstrongspanProcess Improvement/span/strongspanspan: Apply Agile, Lean, and Fast-Flow principles to improve team efficiency and the delivery of high-quality data collection solutions./span/spanspan /span/p/li/ul/divdivullipstrongspanSupport Company Vision and Values/span/strongspanspan: Model and promote behaviors that align with the company's vision and values. Participate actively in company-wide initiatives and projects as /spanspanrequired/spanspan./span/spanspan /span/p/li/ul/divdivpspan /span/p/divdivpstrongspanExperience, Skills and Qualifications/span/strongspan /span/p/divdivullipspanspanBachelor's, Master's, or PhD in Computer Science, /spanspanMathematics, /spanspanData Science, or /spanspana related field/spanspan./span/spanspan /span/p/li/ul/divdivullipspanspan6#43; years of experience in software engineering, with a focus on AI amp; ML technologies, particularly in data collection and unstructured data processing./span/spanspan /span/p/li/ul/divdivullipspanspan3/spanspan#43; years of experience in a leadership role/spanspan /spanspanmanaging individual contributors./span/spanspan /span/p/li/ul/divdivullipspanspanStrong /spanspanexpertise/spanspan in NLP and machine learning, with hands-on experience in classifiers, large language models (LLMs), and other NLP techniques./span Additionally experience in Gen AI, RAG, Agentic AI is essential/span/p/li/ul/divdivullipspanspanExtensive experience with data pipeline and messaging technologies such as Apache Kafka, Airflow, and cloud data platforms (e.g., Snowflake)./span/spanspan /span/p/li/ul/divdivullipspanspanExpert-level /spanspanproficiency/spanspan in Java, Python, SQL, and other relevant programming languages and tools./span/spanspan /span/p/li/ul/divdivullipspanspanStrong understanding of cloud-native technologies and containerization (e.g., Kubernetes, Docker) with experience in managing these systems globally./span/spanspan /span/p/li/ul/divdivullipspanspanDemonstrated ability to solve complex technical challenges and deliver scalable solutions./span/spanspan /span/p/li/ul/div/divdivdivullipspanspanExcellent communication skills with a collaborative approach to working with/spanspan global/spanspan teams and stakeholders./span/spanspan /span/p/li/ul/divdivullipspanspanExperience working in fast-paced environments, particularly in industries that rely on data-intensive technologies (experience in fintech is highly desirable)./span/spanspanspan /span/spanbr /span /span/p/li/ul/divdivpstrongspanWorking Conditions/span/strongspanspan /span/spanspan /span/p/divdivpspanspanThe job conditions for this position are in a standard office setting. /spanspanEmployees in this position use PC and phone/spanspans/spanspan on an ongoing basis throughout the day./spanspan Limited corporate travel may be /spanspanrequired/spanspan to remote offices or other business meetings and events./span/spanspan /span/p/div/divpbr /spanMorningstar is an equal opportunity employer./span/ppMorningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues./pI10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal Entity]] Financial Services Full-time Mumbai India IN https://mygwork.com/jobs/morningstar-engineering-manager-data-science-and-machine-learning-1?src=linkedinutm_source=linkedinutm_medium=referralutm_campaign=jobs Morningstar
![CDATA[ p strong em This job is with Morningstar, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. /em /strong /p divdivpspanspanAs an Engineering Manager, AI amp; ML (Data Collection), you will play a vital role in /spanspanexecuting/spanspan the company's AI and machine learning initiatives with a strong focus on data collection technologies. This position will require deep technical /spanspanexpertise/spanspan in unstructured data processing, data collection pipeline engineering, and a hands-on approach to managing and mentoring engineers. Your leadership will ensure that AI amp; ML data collection systems are developed and operationalized at the highest standards of performance, reliability, and security. You will be working closely with individual contributors, ensuring that projects align with broader business goals and AI/ML strategies./span/spanspan /span/p/divdivpspan /span/p/divdivpspanspanThis role requires deep /spanspanengagement/spanspan in the design, development, and maintenance /spanspanof AI amp; ML models, solutions, architecture, and services/spanspan. You will need to provide strong technical direction, problem-solve complex technical challenges, and ensure that the team consistently delivers high-quality, scalable solutions/spanspan./spanspan /spanspanYou will /spanspanleverage/spanspan your deep knowledge in areas such as advanced natural language processing (NLP)/spanspan, generative AI (GenAI)/spanspan and/spanspan large language models (LLMs), /spanspanML Operations (/spanspanMLOps/spanspan), data architecture, /spanspandata pipelines, and cloud-managed services/spanspan./span/spanspan /span/p/divdivpspan /span/p/divdivpspanspanYour leadership will ensure that our AI/ML systems align with/spanspan /spanspanglobal business strategies, /spanspanmaintaining/spanspan seamless integration and high-performance standard/spanspans/spanspan./spanspan /spanspanYou will oversee the end-to-end lifecycle of AI/ML data systems-from research and development to deployment and operationalization/spanspan./span/spanspan /span/p/divdivpspan /span/p/divdivpspanspanYou will /spanspanbe responsible for/spanspan mentoring team members, resolving technical challenges, and fostering a culture of innovation and collaboration/spanspan while /spanspanensuring they have the right tools, frameworks, and guidance to succeed/spanspan. This role offers a unique opportunity to drive impactful change in a fast-paced, dynamic environment, where your efforts will directly contribute to the success of our AI/ML initiatives globally/spanspan./spanspan /spanspanYour ability to collaborate with /spanspancross-departmental stakeholders/spanspan, provide leadership across locations, set /spanspanhigh standards/spanspan for the team, and hire, train, and /spanspanretain/spanspan exceptional talent is foundational to your success. You will /spanspansolicit/spanspan feedback, engage others with empathy, inspire creative thinking, and help foster a culture of belonging, teamwork, and purpose/spanspan./span/spanspan /span/p/divdivpspan /span/p/divdivpstrongspanTeam/spanspan Overview/span/strongspan /span/p/divdivpspanspanYou will lead a multidisciplinary team of engineers and data scientists responsible /spanspanfor building AI amp; ML /spanspansolutions and /spanspanservices/spanspan as part of robust /spanspandata collection pipelines /spanspanhandling /spanspanlarge volumes of unstructured data. Your team will focus on building scalable and reliable systems to process and categorize data that is essential for downstream /spanspandata collection processing./span/spanspan /span/p/divdivpspan /span/p/divdivpstrongspanOutline of Duties and Responsibilities/span/strongspan /span/p/divdivullipstrongspanAI amp; ML Data Collection Leadership/span/strongspanspan: Drive the execution of AI amp; ML initiatives related to data collection, ensuring that the team's efforts are aligned with overall business goals and strategies./span/spanspan /span/p/li/ul/div/divdivdivullipstrongspanTechnical Oversight/span/strongspanspan: Provide hands-on technical leadership in the engineering of ML models and services, focusing on unstructured data, NLP, and classifiers. Oversee and contribute to the implementation of scalable solutions that meet /spanspanhigh standards/spanspan of reliability and efficiency./span/spanspan /span/p/li/ul/divdivullipstrongspanTeam Leadership amp; Development/span/strongspanspan: Lead, mentor, and develop a high-performing team of engineers and data scientists, fostering a culture of innovation and continuous improvement. Ensure effective communication and coordination within your team and across geographically dispersed teams./span/spanspan /span/p/li/ul/divdivullipstrongspanNLP Technologies/span/strongspanspan: Contribute to the development and application of NLP techniques, including classifiers, transformers, LLMs, and other methodologies, to efficiently process and categorize unstructured data. Ensure these models are integrated seamlessly into the broader AI/ML infrastructure./span/spanspan /span/p/li/ul/divdivullipstrongspanData Pipeline Engineering/span/strongspanspan: Design, develop, and /spanspanmaintain/spanspan advanced data collection pipelines, /spanspanutilizing/spanspan orchestration, messaging, database, and data platform technologies. Ensure pipelines are /spanspanoptimized/spanspan for scalability, performance, and reliability./span/spanspan /span/p/li/ul/divdivullipstrongspanCross-functional Collaboration/span/strongspanspan: Work closely with other AI/ML teams, data collection engineering teams, product management, and others to ensure data collection efforts support broader AI/ML goals and product /spanspanobjectives/spanspan./span/spanspan /span/p/li/ul/divdivullipstrongspanInnovation amp; Continuous Improvement/span/strongspanspan: Continuously explore and implement /spanspannew technologies/spanspan and methodologies to enhance the efficiency and accuracy of data collection and processing systems. Stay at the forefront of advancements in NLP and data processing./span/spanspan /span/p/li/ul/divdivullipstrongspanSystem Integrity amp; Security/span/strongspanspan: Ensure that all data collection systems meet the highest standards of integrity, security, and compliance. Implement best practices for data governance and model transparency./span/spanspan /span/p/li/ul/divdivullipstrongspanTalent Acquisition amp; Retention/span/strongspanspan: Play an active role in recruiting, training, and /spanspanretaining/spanspan top engineering talent. Foster an environment where team members are encouraged to innovate, feel valued, and achieve their full potential./span/spanspan /span/p/li/ul/divdivullipstrongspanProcess Improvement/span/strongspanspan: Apply Agile, Lean, and Fast-Flow principles to improve team efficiency and the delivery of high-quality data collection solutions./span/spanspan /span/p/li/ul/divdivullipstrongspanSupport Company Vision and Values/span/strongspanspan: Model and promote behaviors that align with the company's vision and values. Participate actively in company-wide initiatives and projects as /spanspanrequired/spanspan./span/spanspan /span/p/li/ul/divdivpspan /span/p/divdivpstrongspanExperience, Skills and Qualifications/span/strongspan /span/p/divdivullipspanspanBachelor's, Master's, or PhD in Computer Science, /spanspanMathematics, /spanspanData Science, or /spanspana related field/spanspan./span/spanspan /span/p/li/ul/divdivullipspanspan6#43; years of experience in software engineering, with a focus on AI amp; ML technologies, particularly in data collection and unstructured data processing./span/spanspan /span/p/li/ul/divdivullipspanspan3/spanspan#43; years of experience in a leadership role/spanspan /spanspanmanaging individual contributors./span/spanspan /span/p/li/ul/divdivullipspanspanStrong /spanspanexpertise/spanspan in NLP and machine learning, with hands-on experience in classifiers, large language models (LLMs), and other NLP techniques./span Additionally experience in Gen AI, RAG, Agentic AI is essential/span/p/li/ul/divdivullipspanspanExtensive experience with data pipeline and messaging technologies such as Apache Kafka, Airflow, and cloud data platforms (e.g., Snowflake)./span/spanspan /span/p/li/ul/divdivullipspanspanExpert-level /spanspanproficiency/spanspan in Java, Python, SQL, and other relevant programming languages and tools./span/spanspan /span/p/li/ul/divdivullipspanspanStrong understanding of cloud-native technologies and containerization (e.g., Kubernetes, Docker) with experience in managing these systems globally./span/spanspan /span/p/li/ul/divdivullipspanspanDemonstrated ability to solve complex technical challenges and deliver scalable solutions./span/spanspan /span/p/li/ul/div/divdivdivullipspanspanExcellent communication skills with a collaborative approach to working with/spanspan global/spanspan teams and stakeholders./span/spanspan /span/p/li/ul/divdivullipspanspanExperience working in fast-paced environments, particularly in industries that rely on data-intensive technologies (experience in fintech is highly desirable)./span/spanspanspan /span/spanbr /span /span/p/li/ul/divdivpstrongspanWorking Conditions/span/strongspanspan /span/spanspan /span/p/divdivpspanspanThe job conditions for this position are in a standard office setting. /spanspanEmployees in this position use PC and phone/spanspans/spanspan on an ongoing basis throughout the day./spanspan Limited corporate travel may be /spanspanrequired/spanspan to remote offices or other business meetings and events./span/spanspan /span/p/div/divpbr /spanMorningstar is an equal opportunity employer./span/ppMorningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues./pI10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal Entity]]
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