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Manager Machine Learning Finance Jobs in Idaho (NOW HIRING)

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As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

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As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

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Manager Machine Learning Finance information

What does a manager of machine learning in finance do?

A Manager of Machine Learning in Finance oversees teams that develop and implement machine learning models to solve financial problems, such as risk assessment, fraud detection, and algorithmic trading. They coordinate with data scientists, engineers, and business stakeholders to ensure models meet regulatory standards and align with company goals. Additionally, they are responsible for project management, mentoring team members, and staying updated with advancements in both finance and artificial intelligence.

How does a manager of machine learning in finance typically collaborate with cross-functional teams?

A Manager of Machine Learning in Finance often works closely with data scientists, software engineers, financial analysts, and business stakeholders. They are responsible for translating business problems into machine learning solutions and ensuring models meet both technical and regulatory requirements. Regular meetings and clear communication are essential, as the manager must align team efforts with organizational goals, facilitate knowledge sharing, and integrate model outputs into financial decision-making processes. Collaboration also involves coordinating with IT for data infrastructure and with compliance teams to uphold data privacy standards.

What are the key skills and qualifications needed to thrive as a manager of machine learning in finance, and why are they important?

To thrive as a Manager of Machine Learning in Finance, you need strong expertise in machine learning, statistics, and financial analysis, typically supported by a relevant advanced degree and experience in both data science and finance. Familiarity with programming languages like Python or R, cloud platforms, and machine learning frameworks such as TensorFlow or Scikit-learn is essential, along with knowledge of regulatory compliance systems. Exceptional leadership, strategic thinking, and communication skills set top candidates apart by enabling effective team management and cross-functional collaboration. These skills and qualities are crucial to drive innovative solutions, ensure regulatory adherence, and deliver business value in a complex financial environment.

What is the difference between Manager Machine Learning Finance vs Data Scientist Finance?

AspectManager Machine Learning FinanceData Scientist Finance
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or Finance; certifications in machine learning or data analysisBachelor's or Master's in Data Science, Statistics, or related fields; often includes certifications in data analysis or programming
Work EnvironmentLeads teams, manages projects, collaborates with stakeholders in financeAnalyzes data, develops models, supports decision-making in finance teams
Employer & Industry UsageFinancial institutions, hedge funds, investment firmsFinancial firms, banks, fintech companies

The Manager Machine Learning Finance oversees teams and projects applying machine learning to finance problems, focusing on leadership and strategy. In contrast, Data Scientists in finance primarily analyze data and develop models to support financial decisions. Both roles require strong technical skills, but the manager role emphasizes team management and project oversight.

Can manager machine learning finance be used in finance?

A Manager of Machine Learning in Finance oversees the development and implementation of machine learning models to improve financial analysis, risk management, and trading strategies. This role involves skills in data science, programming, and finance, and is used to enhance decision-making processes and automate tasks within financial institutions.

What cities in Idaho are hiring for Manager Machine Learning Finance jobs?

Cities in Idaho with the most Manager Machine Learning Finance job openings:

Manager Machine Learning Finance jobs near you

Principal Machine Learning Engineer

Micron Technology, Inc

Boise, ID • On-site

$150 - $210/hr

Other

Medical, Dental, Vision, PTO

Posted 7 days ago

Micron Technology rating

8.6

Company rating: 8.6 out of 10

Based on 43 frontline employees who took The Breakroom Quiz

27th of 159 rated electronics manufacturers

Job description

Req ID: JR106544 Principal Machine Learning Engineer

Our vision is to transform how the world uses information to enrich life for all.

Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.

The Smart Manufacturing and AI team at Micron Technology is looking for an ambitious Machine Learning Engineer. Are you curious, high velocity, and ready to solve complex problems? Do you dream in data science and machine learning models? If so, we want you to join us!

Our mission is to enable to deliver industry-winning machine learning solutions to power Micron’s dominance in the highly competitive memory solutions market! As a Principal Machine Learning Engineer, will have experience in a variety of data and cloud technologies and have extensive practice modeling data, querying, and deploying scalable pipelines to execute machine learning models.

You will collaborate with Data Scientists, ML Engineers, Data Engineers, and expert users to build and deploy scalable AI/ML solutions that drive value and insight from Micron’s manufacturing processes and systems.

Responsibilities:
  • Design, build, and continuously refine ML models to address business challenges and enhance product capabilities.
  • Analyze large datasets to uncover patterns, trends, and insights that inform and improve machine learning models.
  • Stay ahead of advancements in AI/ML and integrate emerging techniques into the MLOps lifecycle.
  • Build and maintain robust, scalable data pipelines and infrastructure to support model training and deployment.
  • Collaborate on data preprocessing and feature engineering to improve input data quality and model performance.
  • Design and optimize data architectures across cloud platforms (Snowflake, GCP, Azure) for AI/ML use cases.
  • Develop custom applications and implement CI/CD pipelines to support efficient ML solution deployment.
  • Deploy, evaluate, and monitor models in production, balancing performance with cost efficiency and enabling continuous improvement.
  • Partner with Product and Engineering teams to define and implement Generative AI integration strategies and roadmaps.
  • Communicate insights and collaborate multi-functionally, translating complex analytics into actionable recommendations for diverse collaborators.
  • Drive the technical vision and lead end-to-end execution of complex, multi-functional AI/ML projects.
  • Mentor and coach developing and senior team members, elevating the overall technical competence of the engineering team.
  • Embrace and champion AI-assisted software development such as Opencode, Copilot; while strictly managing and auditing AI agents to ensure production quality code that is reliable, secure and high quality.
Minimum Qualifications:
  • Master's or PhD degree in Computer Science, Machine Learning, Data Science, Statistics, or a field closely related to AI and Machine Learning with 8+ years (or PhD with 5+ years) experience building end-to-end ML systems on cloud platforms, automating model training, testing, and deployment.
  • Strong experience with ML frameworks (scikit-learn, TensorFlow, PyTorch) and core techniques including regression, classification, deep learning, reinforcement learning, and generative AI.
  • Proficient in Python or Java, with experience developing APIs and event-driven pipelines using Kafka, Pub/Sub, or similar messaging systems.
  • Skilled in scalable data engineering, including ETL/ELT pipelines (Kubeflow, Airflow, Dataflow), SQL, and data architecture design.
  • Hands-on experience with cloud and DevOps tools (GCP, AWS, Azure, Docker, Kubernetes), combined with strong analytical, communication, and collaboration skills.
  • Proven track record of technical leadership, including leading ML project delivery and mentoring engineering teams.
Preferred Qualifications:
  • Strong foundation in machine learning and deep learning, with solid grounding in probability and statistics.
  • Proven ability to productionize data science prototypes into scalable, real-world solutions.
  • Advanced experience using and managing GenAI coding assistants, with a strong ability to peer-review and rigorously test AI-generated code logic.
  • Hands-on experience building Generative AI solutions and intelligent agents (ADK, LangChain/LangGraph, CrewAI, DsPy, Semantic Kernel).
  • Expertise in semantic search and retrieval systems, including RAG, GraphRAG, NLP, prompt engineering, and LLM fine-tuning/evaluation.
  • Experience with end-to-end data and engineering workflows: ETL pipelines, big data processing, databases (BigQuery, Snowflake, MSSQL, PostgreSQL), and CI/CD tools (Git, Docker, Kubernetes, Jenkins) and MLOps/CE platforms (MLflow, Kubeflow, Vertex AI, SageMaker, TFX)
Job Profile(s):

Machine Learning Engineer 5

Relocation Level: TBD

Before Getting Started

Please review Micron’s Internal Job Application Policy on your regional PeopleNow Career Opportunities page before searching and applying for jobs. Note in particular that:

  • Hiring managers may view your performance appraisals, original resume, transcripts or other performance-related documentation in your personal file. This information will be held in confidence.
  • If you are selected to interview for a position, you must notify your direct supervisor before participating in the interview process.
Benefits
  • Micron benefits are designed to help you stay well, provide peace of mind and help you prepare for the future.
  • We offer a choice of medical, dental and vision plans in all locations enabling team members to select the plans that best meet their family healthcare needs and budget.
  • Micron also provides benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave.
  • Additionally, Micron benefits include a robust paid time-off program and paid holidays.

Micron is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, citizenship status, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws.

To request assistance with the application process and/or for reasonable accommodations, please contact Micron’s People Organization at hrsupport_na@micron.com or 1-800-336-8918 (select option #3)

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