Sr. Machine Learning Engineer
Kasmo Global
Please make sure to submit 3 to 4 genuine profiles at the earliest.
I wont accept opts with internships
Actalent/Peyton
We received a new role from Toyota. Max rate is 95/hr. Toyota Connected's Mobility team is looking for a 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:
- Write clean, maintainable code while complying with coding standards
- Establish scalable, efficient, automated processes for large scale data analysis, model development, model validation and model implementation
- Drive adoption of best practices across organizations
- Deliver production-ready code
- Work with Product Owners to define the KPIs for machine learning projects
- 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
- Prepare and present findings to both technical and non-technical audiences
- Work within the constraints of time, budget, and resources capacities to align with Toyota's global vision
- Develop and foster collaborative relationships with product, business, and engineering teams to effectively serve our customer needs
Required Qualifications:
- 5+ years of hands-on experience in Machine Learning in a corporate environment
- Spark and EMR for large ETL jobs
- Working with ETL tasks using optimized Databricks queries
- Designing, implementing, monitoring, and updating ML pipelines using SageMaker or MAF
- SageMaker for data cleaning, model selection, model training, and optimization
- Other AWS Services - S3, DynamoDB, Lambda, Kinesis, API GW,
- MLFlow for model metric and artifact generation and monitoring
- Combining data from multiple datasets
- Developing CI/CD pipelines, unit and functional testing
- Establishing model monitoring and model update pipelines
- Strong decision-making skills with the ability to analyze data, assess risks, and implement effective solutions in a fast-paced environment
- Problem-solving skills with the ability to identify challenges, develop creative solutions, and implement effective strategies
- Proven ability to learn and apply new technologies, programming practices, patterns, and methods
- Experience collaborating effectively with cross-functional teams, including developers, designers, and product owners
- Experience taking ownership of assigned projects and tasks, proactively driving them to completion while ensuring accountability for quality and deadlines.
- Results-driven with a strong track record of setting goals, executing strategies, and delivering measurable outcomes
I in the Hiring Process
cceptable Uses of AI:
- Cover Letter and Resume Creation: AI tools may be used to assist in drafting cover letters and resumes, provided that the final documents truthfully reflect the candidate's own experiences, skills, and accomplishments
- Interview Preparation: Candidates may use AI-powered tools to practice common interview questions or receive feedback on their responses
- Completing Skills Assessments: Candidates must not use AI tools to complete coding exercises, technical challenges, or any other assessments that evaluate their skills directly
- Answering Questions: Candidates must not use AI tools to generate answers to interview questions, whether they are technical or behavioral. All responses during an interview must be entirely their own
Vacancy posted 3 days ago
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