Fidelity TalentSource LLC
Fidelity TalentSource LLC | Principal, AI/ML Engineer MA
Fidelity TalentSource LLC, Boston, Massachusetts, us, 02298
Job Description:
Principal Software Engineer, Machine Learning
As a Machine Learning Engineer, build and maintain large scale ML Infrastructure and ML pipelines. Contribute to building advanced analytics, machine learning platform and tools to enable both prediction and optimization of models. Extend existing ML Platform and frameworks for scaling model training & deployment. Partner closely with various business & engineering teams to drive the adoption, integration of model outputs. This role is a critical element to using the power of Data Science in delivering Fidelity s promise of creating the best customer experiences in financial services. The Team Enterprise Data Science Platform team (part of Enterprise Technology BU) is focused on delivery data and ML solutions for the organization. As part of this team, you will be responsible for building advanced analytics solutions using various cloud technologies and collaborating with Data Scientists to robustly scale up ML Models to large volumes in production. The Expertise You Have Has Bachelor s or Master s Degree in a technology related field (e.g. Engineering, Computer Science, etc.). 8+ years of proven experience in implementing Big data solutions in data analytics space. 2+ years of experience in developing ML infrastructure and MLOps in the Cloud using AWS Sagemaker. Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required. Experience in Object Oriented Programming (Java, Scala, Python), SQL, Unix scripting or related programming languages and exposure to some of Python s ML ecosystem (numpy, panda, sklearn, tensorflow, etc.). Experience with building data pipelines in getting the data required to build and evaluate ML models, using tools like Apache Spark or other distributed data processing frameworks. Data movement technologies (ETL/ELT), Messaging/Streaming Technologies (AWS SQS, Kinesis/Kafka), Relational and NoSQL databases (DynamoDB, EKS, Graph database), API and in-memory technologies. Strong knowledge of developing highly scalable distributed systems using Open-source technologies. Experience with CI/CD tools (e.g., Jenkins or equivalent), version control (Git), orchestration/DAGs tools (AWS Step Functions, Airflow, Luigi, Kubeflow, or equivalent). Solid experience in Agile methodologies (Kanban and SCRUM). The Skills You Bring
You have strong technical design and analysis skills. You the ability to deal with ambiguity and work in fast paced environment. Your experience supporting critical applications. You are familiar with applied data science methods, feature engineering and machine learning algorithms. Your Data wrangling experience with structured, semi-structure and unstructured data. Your experience building ML infrastructure, with an eye towards software engineering. You have excellent communication skills, both through written and verbal channels. You have excellent collaboration skills to work with multiple teams in the organization. Your ability to understand and adapt to changing business priorities and technology advancements in Big data and Data Science ecosystem. The Value You Deliver
Designing & developing a feature generation & store framework that promotes sharing of data/features among different ML models. Partner with Data Scientists and to help use the foundational platform upon which models can be built and trained. Operationalize ML Models at scale (e.g. Serve predictions on tens of millions of customers). Build tools to help detect shifts in data/features used by ML models to help identify issues in advance of deteriorating prediction quality, monitoring the uncertainty of model outputs, automating prediction explanation for model diagnostics. Exploring new technology trends and leveraging them to simplify our data and ML ecosystem. Driving Innovation and implementing solutions with future thinking. Guiding teams to improve development agility and productivity. Resolving technical roadblocks and mitigating potential risks. Delivering system automation by setting up continuous integration/continuous delivery pipelines. Certifications: Company Overview Fidelity Investments is a privately held company with a mission to strengthen the financial well-being of our clients. We help people invest and plan for their future. We assist companies and non-profit organizations in delivering benefits to their employees. And we provide institutions and independent advisors with investment and technology solutions to help invest their own clients money. Join Us At Fidelity, you ll find endless opportunities to build a meaningful career that positively impacts peoples lives, including yours. You can take advantage of flexible benefits that support you through every stage of your career, empowering you to thrive at work and at home. Honored with a Glassdoor Employees Choice Award, we have been recognized by our employees as a top 10 Best Place to Work in 2024. And you don t need a finance background to succeed at Fidelity\u2014we offer a range of opportunities for learning so you can build the career you ve always imagined. Fidelity s hybrid working model blends the best of both onsite and offsite work experiences. Having the majority of our associates work onsite is important for our business strategy and our culture. We also value the benefits that working offsite offers associates. Most roles listed as Hybrid will require associates to work onsite all business days of every other week in a Fidelity office. This does not apply to roles listed as Remote or Onsite.
At Fidelity, we value honesty, integrity, and the safety of our associates and customers within a heavily regulated industry . Certain roles may require candidates to go through a preliminary credit check during the screening process. Candidates who are presented with a Fidelity offer will need to go through a background investigation, detailed in this document, and may be asked to provide additional documentation as requested. This investigation includes but is not limited to a criminal, civil litigations and regulatory review, employment, education, and credit review (role dependent). These investigations will account for 7 years or more of history, depending on the role. Where permitted by federal or state law, Fidelity will also conduct a pre-employment drug screen, which will review for the following substances: Amphetamines, THC (marijuana), cocaine, opiates, phencyclidine.
We invite you to
Find Your Fidelity
at fidelitycareers.com.
Fidelity Investments is an equal opportunity employer. We believe that the most effective way to attract, develop and retain a diverse workforce is to build an enduring culture of inclusion and belonging. Fidelity will reasonably accommodate applicants with disabilities who need adjustments to participate in the application or interview process. To initiate a request for an accommodation, contact the HR Accommodation Team by sending an email to accommodations@fmr.com.
Principal Software Engineer, Machine Learning
As a Machine Learning Engineer, build and maintain large scale ML Infrastructure and ML pipelines. Contribute to building advanced analytics, machine learning platform and tools to enable both prediction and optimization of models. Extend existing ML Platform and frameworks for scaling model training & deployment. Partner closely with various business & engineering teams to drive the adoption, integration of model outputs. This role is a critical element to using the power of Data Science in delivering Fidelity s promise of creating the best customer experiences in financial services. The Team Enterprise Data Science Platform team (part of Enterprise Technology BU) is focused on delivery data and ML solutions for the organization. As part of this team, you will be responsible for building advanced analytics solutions using various cloud technologies and collaborating with Data Scientists to robustly scale up ML Models to large volumes in production. The Expertise You Have Has Bachelor s or Master s Degree in a technology related field (e.g. Engineering, Computer Science, etc.). 8+ years of proven experience in implementing Big data solutions in data analytics space. 2+ years of experience in developing ML infrastructure and MLOps in the Cloud using AWS Sagemaker. Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required. Experience in Object Oriented Programming (Java, Scala, Python), SQL, Unix scripting or related programming languages and exposure to some of Python s ML ecosystem (numpy, panda, sklearn, tensorflow, etc.). Experience with building data pipelines in getting the data required to build and evaluate ML models, using tools like Apache Spark or other distributed data processing frameworks. Data movement technologies (ETL/ELT), Messaging/Streaming Technologies (AWS SQS, Kinesis/Kafka), Relational and NoSQL databases (DynamoDB, EKS, Graph database), API and in-memory technologies. Strong knowledge of developing highly scalable distributed systems using Open-source technologies. Experience with CI/CD tools (e.g., Jenkins or equivalent), version control (Git), orchestration/DAGs tools (AWS Step Functions, Airflow, Luigi, Kubeflow, or equivalent). Solid experience in Agile methodologies (Kanban and SCRUM). The Skills You Bring
You have strong technical design and analysis skills. You the ability to deal with ambiguity and work in fast paced environment. Your experience supporting critical applications. You are familiar with applied data science methods, feature engineering and machine learning algorithms. Your Data wrangling experience with structured, semi-structure and unstructured data. Your experience building ML infrastructure, with an eye towards software engineering. You have excellent communication skills, both through written and verbal channels. You have excellent collaboration skills to work with multiple teams in the organization. Your ability to understand and adapt to changing business priorities and technology advancements in Big data and Data Science ecosystem. The Value You Deliver
Designing & developing a feature generation & store framework that promotes sharing of data/features among different ML models. Partner with Data Scientists and to help use the foundational platform upon which models can be built and trained. Operationalize ML Models at scale (e.g. Serve predictions on tens of millions of customers). Build tools to help detect shifts in data/features used by ML models to help identify issues in advance of deteriorating prediction quality, monitoring the uncertainty of model outputs, automating prediction explanation for model diagnostics. Exploring new technology trends and leveraging them to simplify our data and ML ecosystem. Driving Innovation and implementing solutions with future thinking. Guiding teams to improve development agility and productivity. Resolving technical roadblocks and mitigating potential risks. Delivering system automation by setting up continuous integration/continuous delivery pipelines. Certifications: Company Overview Fidelity Investments is a privately held company with a mission to strengthen the financial well-being of our clients. We help people invest and plan for their future. We assist companies and non-profit organizations in delivering benefits to their employees. And we provide institutions and independent advisors with investment and technology solutions to help invest their own clients money. Join Us At Fidelity, you ll find endless opportunities to build a meaningful career that positively impacts peoples lives, including yours. You can take advantage of flexible benefits that support you through every stage of your career, empowering you to thrive at work and at home. Honored with a Glassdoor Employees Choice Award, we have been recognized by our employees as a top 10 Best Place to Work in 2024. And you don t need a finance background to succeed at Fidelity\u2014we offer a range of opportunities for learning so you can build the career you ve always imagined. Fidelity s hybrid working model blends the best of both onsite and offsite work experiences. Having the majority of our associates work onsite is important for our business strategy and our culture. We also value the benefits that working offsite offers associates. Most roles listed as Hybrid will require associates to work onsite all business days of every other week in a Fidelity office. This does not apply to roles listed as Remote or Onsite.
At Fidelity, we value honesty, integrity, and the safety of our associates and customers within a heavily regulated industry . Certain roles may require candidates to go through a preliminary credit check during the screening process. Candidates who are presented with a Fidelity offer will need to go through a background investigation, detailed in this document, and may be asked to provide additional documentation as requested. This investigation includes but is not limited to a criminal, civil litigations and regulatory review, employment, education, and credit review (role dependent). These investigations will account for 7 years or more of history, depending on the role. Where permitted by federal or state law, Fidelity will also conduct a pre-employment drug screen, which will review for the following substances: Amphetamines, THC (marijuana), cocaine, opiates, phencyclidine.
We invite you to
Find Your Fidelity
at fidelitycareers.com.
Fidelity Investments is an equal opportunity employer. We believe that the most effective way to attract, develop and retain a diverse workforce is to build an enduring culture of inclusion and belonging. Fidelity will reasonably accommodate applicants with disabilities who need adjustments to participate in the application or interview process. To initiate a request for an accommodation, contact the HR Accommodation Team by sending an email to accommodations@fmr.com.