Vetted HealthCincinnati
Travel Clinical Laboratory Scientist ($2700-$3200/Week) Company: Vetted Health States: All 50 states “(nationwide)” Overview: Vetted Health is actively hiring Travel Clinical Laboratory Scientist for 13-week assignments across the United States....
DoorDashColerain Township
Available in over 4,000cities in the U.S, DoorDash connects local businesses and localdrivers (called Dashers) with opportunities to earn, work, andlive.All you need is a mode oftransportation (bike, car, scooter) and a smartphone to startmaking money.You can even sign up and beginworking that same ...
DoorDashColerain Township
Available in over 4,000cities in the U.S, DoorDash connects local businesses and localdrivers (called Dashers) with opportunities to earn, work, andlive.All you need is a mode oftransportation (bike, car, scooter) and a smartphone to startmaking money.You can even sign up and beginworking that same ...
Intelliswift Software IncCincinnati
science, preferably in Microbiology, Biology, or Natural Science.
Experience:
Typically requires a minimum of 2 years of experience performing tests or analyses for pharmaceutical raw materials, finished products, or microbiological samples. Experience...
Integrated Resources, IncCincinnati
the necessary compliance status required by company and facility standards.
Education:
Bachelor’s degree in physical science, preferably in Microbiology, Biology, or Natural Science.
Experience:
Typically requires a minimum of 2 years of experience...
Talent Software Services, Inc.Cincinnati
Must haves: " experience with an interest in Data. " Previous R&D management-track Nice to haves: " Ability to translate high level business needs into more specific requirements for IT teams to develop against (in partnership with a Business...
KBP FoodsFairfield
Are you ready to take your career to the next level while savoring the delicious taste of success? Look no further than KBP Foods, where we're searching for energetic and passionate individuals to join our KFC Team as Team Members! If you have a hunger for success and a passion for serving up finger...
Great American Insurance GroupCincinnati
and business units, providing strategic insights and recommendations to drive business outcomes.
• Lead and mentor a team of 25-30 analysts in the predictive analytics and data science domains.
• Develop and deliver predictive pricing models that accurately...
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Senior Machine Learning Engineer
Cincinnati | www.resume-library.com |
Seeking a Senior Machine Learning Engineer for a long term contract role with a leading US retail company. This is a hybrid position based in Cincinnati, OH.
Job Description
The Senior Machine Learning Engineer will lead the integration and operationalization of machine learning models. This role requires collaboration with data scientists and leadership teams, and a strong foundation in MLOps methodologies. Experience in diverse Client platforms, including Google Vertex AI and other cloud and open-source technologies, is essential.
The candidate will bridge MLOps, data science, and leadership to ensure the smooth functioning of the organization's Client infrastructure.
Qualifications
Minimum of 4 years of experience in MLOps, with a demonstrated ability to work with various Client platforms.
Strong proficiency in Python and familiarity with data science methodologies.
Experience with cloud technologies, particularly Google Cloud and Vertex AI, and adaptability to technologies like Microsoft Azure or open-source tools.
Excellent communication skills, capable of bridging technical and business domains
Experience in developing state-of-the-art techniques for multi-stage, personalized, context-aware, and sequential recommender systems.
Hands-on experience working on recommender systems, drawing from Client techniques such as embedding based retrieval, reinforcement learning, transformers, and LLMs.
Capable software engineering skills to lead a multi stage recommender system model lifecycle from inception to production.
Key Responsibilities
Collaborate with data scientists to understand their needs and integrate their models into production systems efficiently.
Act as a liaison between data science, MLOps, and leadership teams to facilitate communication and goal alignment.
Develop, maintain, and manage scalable MLOps pipelines, particularly leveraging Google Vertex AI.
Implement and manage Google Vertex AI's AutoML for high-quality machine learning models.
Utilize Vertex AI Pipelines for streamlined operations and continuous modeling experiences.
Maintain expertise in Client technologies and platforms, including TensorFlow, PyTorch, scikit-learn, and integrate them with Client frameworks.
Work with various machine learning models such as vision, video, translation, and natural language processing.
Efficiently manage, share, and reuse machine learning features at scale using Vertex AI Feature Store.
Implement feature stores as a central repository for maintaining transparency in Client operations.
Enable feature delivery with endpoint exposure while ensuring authority and security features are maintained.
Assist with data labeling and management to ensure high-quality data for Client models.
Collaborate with data engineers and data scientists to ensure the integrity and efficiency of data used in Client models.
Ensure end-to-end integration for data to AI, including the use of BigTable/BigQuery for executing machine learning models on business intelligence tools.
Monitor Client models in production, identify improvement opportunities, and implement optimizations.
Stay updated with the latest trends in MLOps and Client technologies
Job Description
The Senior Machine Learning Engineer will lead the integration and operationalization of machine learning models. This role requires collaboration with data scientists and leadership teams, and a strong foundation in MLOps methodologies. Experience in diverse Client platforms, including Google Vertex AI and other cloud and open-source technologies, is essential.
The candidate will bridge MLOps, data science, and leadership to ensure the smooth functioning of the organization's Client infrastructure.
Qualifications
Minimum of 4 years of experience in MLOps, with a demonstrated ability to work with various Client platforms.
Strong proficiency in Python and familiarity with data science methodologies.
Experience with cloud technologies, particularly Google Cloud and Vertex AI, and adaptability to technologies like Microsoft Azure or open-source tools.
Excellent communication skills, capable of bridging technical and business domains
Experience in developing state-of-the-art techniques for multi-stage, personalized, context-aware, and sequential recommender systems.
Hands-on experience working on recommender systems, drawing from Client techniques such as embedding based retrieval, reinforcement learning, transformers, and LLMs.
Capable software engineering skills to lead a multi stage recommender system model lifecycle from inception to production.
Key Responsibilities
Collaborate with data scientists to understand their needs and integrate their models into production systems efficiently.
Act as a liaison between data science, MLOps, and leadership teams to facilitate communication and goal alignment.
Develop, maintain, and manage scalable MLOps pipelines, particularly leveraging Google Vertex AI.
Implement and manage Google Vertex AI's AutoML for high-quality machine learning models.
Utilize Vertex AI Pipelines for streamlined operations and continuous modeling experiences.
Maintain expertise in Client technologies and platforms, including TensorFlow, PyTorch, scikit-learn, and integrate them with Client frameworks.
Work with various machine learning models such as vision, video, translation, and natural language processing.
Efficiently manage, share, and reuse machine learning features at scale using Vertex AI Feature Store.
Implement feature stores as a central repository for maintaining transparency in Client operations.
Enable feature delivery with endpoint exposure while ensuring authority and security features are maintained.
Assist with data labeling and management to ensure high-quality data for Client models.
Collaborate with data engineers and data scientists to ensure the integrity and efficiency of data used in Client models.
Ensure end-to-end integration for data to AI, including the use of BigTable/BigQuery for executing machine learning models on business intelligence tools.
Monitor Client models in production, identify improvement opportunities, and implement optimizations.
Stay updated with the latest trends in MLOps and Client technologies
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