Machine Learning Engineer

October 31

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RainesDev

Nearshore Software Development and Staffing and Recruiting

2 - 10 employees

🎯 Recruitment

Description

About Us: We at the forefront of technological innovation, providing tailored software solutions that drive business success. • Job Description: The Machine Learning Engineer will be responsible for designing, implementing, and deploying machine learning models that solve complex problems for our clients. • This role requires an analytical mindset, strong programming skills, and a deep understanding of machine learning algorithms and techniques. • You’ll work collaboratively with data scientists, software engineers, and product managers to deliver engaging solutions that leverage the power of data.

Requirements

Design and develop machine learning models and algorithms to meet business needs. • Collaborate with data scientists to analyze large datasets and extract valuable insights. • Implement and optimize model training processes, ensuring high performance and accuracy. • Deploy models to production and monitor their performance over time. • Work with cross-functional teams to integrate machine learning functionality into applications. • Stay updated on the latest trends and advancements in machine learning and AI technologies. • Bachelor's or Master's degree in Computer Science, Data Science, or a related field. • Minimum of 3 years of experience in machine learning engineering or a similar role. • Proficiency in programming languages such as Python or R. • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, or Scikit-Learn). • Solid understanding of data structures, algorithms, and statistical analysis. • Excellent problem-solving skills and the ability to work collaboratively in a team environment.

Benefits

Competitive salary with annual performance-based bonuses • Comprehensive health, dental, and vision insurance • Gym membership reimbursement or on-site fitness facilities • Paid parental leave for new parents • Employee recognition programs and awards • Flexible working hours and remote work opportunities

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