Mathys+Potestio / The Creative Party®
Machine Learning Engineer
Mathys+Potestio / The Creative Party®, Culver City, California, United States, 90232
Overview Machine Learning Engineer - 3+ years experience. Data Science & AI Team. This is a 12-month, full-time (40 hours/week), hybrid contract role located in Culver City, CA or Cupertino, CA.
Interested in learning more about this job Scroll down and find out what skills, experience and educational qualifications are needed. Summary We are seeking a Machine Learning Engineer to design, develop, and deploy scalable AI/ML models that drive insights and innovation. This role is integral to advancing the team’s initiatives by building data-driven solutions, optimizing performance, and ensuring continuous improvement of deployed systems. Our Ideal Candidate 3+ years of experience in machine learning, AI, or data science Passion for advancing AI technologies with a strong foundation in model development, optimization, and deployment Proficient in Python, R, or Java, with strong problem-solving and analytical skills Familiar with machine learning frameworks (TensorFlow, PyTorch), cloud platforms, and MLOps practices Skilled in collaborating with cross-functional technical and business teams Able to work independently and manage multiple projects simultaneously Flexible and adaptable to changing priorities, timelines, and stakeholders Strong written and verbal communication with exceptional attention to detail Knowledge of reinforcement learning, NLP, computer vision, and big data technologies (Spark, Hadoop, SQL) is a plus Job Description In this role, you will design, train, and implement machine learning models and AI algorithms to support data-driven solutions. You’ll partner with engineering, data, and business stakeholders to deliver scalable models and ensure effective deployment into production environments. This includes preprocessing and analyzing datasets, optimizing model performance, monitoring deployed systems, and maintaining comprehensive documentation. You will also support ongoing improvement of AI/ML processes, frameworks, and infrastructure, contributing to the overall success of the data science team. Education And Experience Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Machine Learning, or a related field Background in deep learning, NLP, or computer vision is highly desirable Experience deploying models with Docker, Kubernetes, or serverless architectures preferred Additional Requirements Please include your resume with application. This opportunity is located in Culver City, CA or Cupertino, CA and requires hybrid work. The pay for this W-2 position is $70.00 per hour. This position may be eligible for PTO, health and dental insurance, and/or 401(k) benefits upon meeting certain length of service and hours requirements. Mathys+Potestio values applicants of all backgrounds and experiences. We do not discriminate based on race, color, national or ethnic origin, ancestry, age, religion or religious creed, disability or handicap, sex or gender, gender identity and/or expression, sexual orientation, military or veteran status, genetic information, or any other characteristic protected under applicable federal, state, or local law.
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Interested in learning more about this job Scroll down and find out what skills, experience and educational qualifications are needed. Summary We are seeking a Machine Learning Engineer to design, develop, and deploy scalable AI/ML models that drive insights and innovation. This role is integral to advancing the team’s initiatives by building data-driven solutions, optimizing performance, and ensuring continuous improvement of deployed systems. Our Ideal Candidate 3+ years of experience in machine learning, AI, or data science Passion for advancing AI technologies with a strong foundation in model development, optimization, and deployment Proficient in Python, R, or Java, with strong problem-solving and analytical skills Familiar with machine learning frameworks (TensorFlow, PyTorch), cloud platforms, and MLOps practices Skilled in collaborating with cross-functional technical and business teams Able to work independently and manage multiple projects simultaneously Flexible and adaptable to changing priorities, timelines, and stakeholders Strong written and verbal communication with exceptional attention to detail Knowledge of reinforcement learning, NLP, computer vision, and big data technologies (Spark, Hadoop, SQL) is a plus Job Description In this role, you will design, train, and implement machine learning models and AI algorithms to support data-driven solutions. You’ll partner with engineering, data, and business stakeholders to deliver scalable models and ensure effective deployment into production environments. This includes preprocessing and analyzing datasets, optimizing model performance, monitoring deployed systems, and maintaining comprehensive documentation. You will also support ongoing improvement of AI/ML processes, frameworks, and infrastructure, contributing to the overall success of the data science team. Education And Experience Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Machine Learning, or a related field Background in deep learning, NLP, or computer vision is highly desirable Experience deploying models with Docker, Kubernetes, or serverless architectures preferred Additional Requirements Please include your resume with application. This opportunity is located in Culver City, CA or Cupertino, CA and requires hybrid work. The pay for this W-2 position is $70.00 per hour. This position may be eligible for PTO, health and dental insurance, and/or 401(k) benefits upon meeting certain length of service and hours requirements. Mathys+Potestio values applicants of all backgrounds and experiences. We do not discriminate based on race, color, national or ethnic origin, ancestry, age, religion or religious creed, disability or handicap, sex or gender, gender identity and/or expression, sexual orientation, military or veteran status, genetic information, or any other characteristic protected under applicable federal, state, or local law.
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