Sr. Machine Learning Engineer ( Need 12+ Exp Profiles)

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Sr. Machine Learning Engineer in Plano, TX (Hybrid) for 6+ months at a pay rate of "unknown." Requires 12+ years of experience, expertise in AWS services, ML pipelines, and strong problem-solving skills.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
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πŸ—“οΈ - Date discovered
August 29, 2025
πŸ•’ - Project duration
More than 6 months
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🏝️ - Location type
Hybrid
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πŸ“„ - Contract type
Unknown
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
Plano, TX
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🧠 - Skills detailed
#MLflow #"ETL (Extract #Transform #Load)" #Programming #DynamoDB #AI (Artificial Intelligence) #Lambda (AWS Lambda) #AWS (Amazon Web Services) #Deep Learning #Monitoring #Data Cleansing #R #Databricks #Spark (Apache Spark) #Datasets #Data Cleaning #ML (Machine Learning) #Scala #S3 (Amazon Simple Storage Service) #SageMaker #Data Analysis #Model Validation #API (Application Programming Interface)
Role description
Job Title: Sr. Machine Learning Engineer Location: Plano, TX (Hybrid) Duration: 6+ months Sr. Machine Learning Engineer who will use machine learning techniques to help us create state-of-the-art solutions for non-trivial, and arguably, unsolved problems. If you are results driven, interested in how to apply advanced Machine Learning techniques, would love to work with next generation generative AI predictive maintenance, are deeply technical, highly innovative, we want to talk to you. Responsibilities: β€’ Write clean, maintainable code while complying with coding standards β€’ β€’ Execute full modeling life cycle including data cleansing, feature creation and iterative model selection β€’ Build scalable, efficient, automated processes for large scale data analysis, model development, model validation and model implementation β€’ Use statistical, machine learning, and deep learning techniques to create scalable solutions and perform R&D to drive discovery of new generation products β€’ Establish scalable, efficient, automated processes for large scale data analysis, model development, model validation and model implementation β€’ Drive adoption of best practices across organizations β€’ Deliver production-ready code β€’ Work with Product Owners to define the KPIs for machine learning projects β€’ Stay abreast of developments in research methodology and changing technologies in the marketplace and proactively identify applications of these latest developments to improve existing methods β€’ Prepare and present findings to both technical and non-technical audiences β€’ Work within the constraints of time, budget, and resources capacities to align with Toyota’s global vision β€’ Develop and foster collaborative relationships with product, business, and engineering teams to effectively serve our customer needs Required Qualifications: β€’ 5+ years of hands-on experience in Machine Learning in a corporate environment β€’ Spark and EMR for large ETL jobs β€’ Working with ETL tasks using optimized Databricks queries β€’ Designing, implementing, monitoring, and updating ML pipelines using SageMaker or MAF β€’ SageMaker for data cleaning, model selection, model training, and optimization β€’ Other AWS Services - S3, DynamoDB, Lambda, Kinesis, API GW, β€’ MLFlow for model metric and artifact generation and monitoring β€’ Combining data from multiple datasets β€’ Developing CI/CD pipelines, unit and functional testing β€’ Establishing model monitoring and model update pipelines β€’ Strong decision-making skills with the ability to analyze data, assess risks, and implement effective solutions in a fast-paced environment β€’ Problem-solving skills with the ability to identify challenges, develop creative solutions, and implement effective strategies β€’ Proven ability to learn and apply new technologies, programming practices, patterns, and methods β€’ Experience collaborating effectively with cross-functional teams, including developers, designers, and product owners β€’ Experience taking ownership of assigned projects and tasks, proactively driving them to completion while ensuring accountability for quality and deadlines. β€’ Results-driven with a strong track record of setting goals, executing strategies, and delivering measurable outcomes