In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
Key Responsibilities
Develop, train, and deploy machine learning models using TensorFlow and Scikit-Learn to address real-world business problems.
Conduct comprehensive data preprocessing, including data cleaning, transformation, and feature engineering to ensure high-quality inputs for model development.
Collaborate with data scientists, data engineers, and business analysts to understand requirements and translate them into scalable ML solutions.
Continuously monitor, evaluate, and refine model performance to ensure accuracy, efficiency, and reliability in production environments.
Document model development processes and proactively communicate technical concepts and results with both technical and non-technical team members.
Stay abreast of the latest research and advancements in machine learning and apply innovative techniques to enhance project outcomes.
Contribute to a culture of knowledge sharing, mentorship, and continuous improvement within the customer's team.
Required Skills and Qualifications
Expert-level proficiency in TensorFlow and Scikit-Learn for end-to-end model development and deployment.
Strong background in data preprocessing, including handling missing values, the hiring company detection, and feature selection.
Excellent written and verbal communication skills, with the ability to convey complex technical information clearly.
Demonstrated experience in designing and implementing production-ready machine learning systems.
Solid understanding of algorithm selection, model evaluation metrics, and performance tuning.
Ability to work independently and remotely, delivering results in a fast-paced, deadline-driven environment.
Detail-oriented with exceptional problem-solving and analytical skills.