QA Engineer (Automation)

Please note this is a hybrid role in Cupertino or Culver City, CA. You must be able to work 3 days onsite (Tuesday, Wednesday, Thursday) and 2 days remote (Monday and Friday).

Ready to make a real impact on a global scale? A leading innovator in technology is seeking a skilled Machine Learning Engineer to join their cutting-edge AI initiatives. As a key member of their team, you will be at the forefront of developing and deploying groundbreaking AI solutions that will shape the future of how people interact with technology. This is your chance to push the boundaries of what's possible and contribute to projects that will touch millions of lives.

In this role, you'll be responsible for designing, developing, and implementing state-of-the-art machine learning models and algorithms. You will leverage your expertise to analyze massive datasets, extract meaningful insights, and train and optimize models for peak performance. Your work will directly impact the development of next-generation AI technologies.

Responsibilities:

• Design, develop, and implement machine learning models and AI algorithms.
• Collect, preprocess, and analyze large datasets.
• Train, optimize, and fine-tune ML models for performance and scalability.
• Deploy ML models into production and ensure continuous monitoring and improvement.
• Develop and maintain documentation for AI/ML models and processes.

Must-Have Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, AI, Machine Learning, or a related field.
• Strong proficiency in programming languages such as Python, R, or Java.
• Experience with machine learning frameworks such as TensorFlow, PyTorch.
• Knowledge of deep learning, natural language processing (NLP), and computer vision.
• Familiarity with cloud platforms and MLOps tools.
• Understanding of data structures, algorithms, and software development best practices.

Nice-to-Have Qualifications:

• Experience with big data technologies like Spark, Hadoop, or SQL-based databases.
• Experience in deploying ML models using Docker, Kubernetes, or serverless architectures.
• Knowledge of reinforcement learning and advanced AI techniques.

The target hiring compensation range for this role is $63 to $70 an hour. Compensation is based on several factors including, but not limited to education, relevant work experience, relevant certifications, and location.

About Aquent Talent:

Aquent Talent connects the best talent in marketing, creative, and design with the world's biggest brands.

Our eligible talent get access to amazing benefits like subsidized health, vision, and dental plans, paid sick leave, and retirement plans with a match. More information on our awesome benefits!

Aquent is an equal-opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics. We're about creating an inclusive environment-one where different backgrounds, experiences, and perspectives are valued, and everyone can contribute, grow their careers, and thrive.

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