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2 months ago
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Requirements and responsibilities
A Senior ML Engineer is responsible for designing, implementing, and maintaining AI systems across various applications. They contribute to the organization's AI strategy, work on complex solutions and optimize existing systems to enhance performance. Responsibilities include mentoring junior ML engineers and collaborating with cross-functional teams.The ideal candidate has at least five years of experience in AI or machine learning with a proven track record of developing and maintaining AI powered products and solutions.Essential Duties and ResponsibilitiesDevelop AI applications and solutions by understanding business needs, collaborating with stakeholders, analyzing data, and implementing AI algorithms.Design, develop, and maintain robust AI systems, including machine learning models and deep learning networks.Document and demonstrate solutions with clear technical documentation, diagrams, and code comments.Contribute to the organization’s AI strategy by researching cutting-edge tools and techniques, participating in educational opportunities, and maintaining professional networks.Identify and resolve performance and scalability issues in AI applications by improving software and addressing bottlenecks and bugs.Lead and collaborate with cross-functional teams to define and implement innovative AI solutions, optimizing user interaction and experience.Conduct code reviews and mentor team members to uphold high coding standards.Translate business requirements into actionable technical requirements.Work closely with data engineering and data science teams to implement automated and unit testing.Improve operations by analyzing systems and recommending procedural changes.Support engineering goals by delivering project outcomes as needed.QualificationsMinimum 5 years of experience in AI and Machine Learning.Demonstrated experience designing and developing AI-powered products in production environments.CompetenciesTechnical Skills:Proficiency in Python, including good experience with AI/ML-related libraries and frameworks.Deep knowledge of AI and machine learning concepts.Good understanding of security, data privacy and regulations compliance considerations in AI systems.Solid experience with one of the major cloud service providers (AWS, Google Cloud, Azure).Knowledge of software design principles and patterns.Proficiency in software testing methodologies.Strong grasp of data structures, algorithms, and computing theory.Soft Skills:Ability to translate business needs into technical solutions.User-centric mindset with focus on outcome and experience.High attention to details and quality.Strong analytical and systematic problem-solving skillsLeadership and teamwork capabilities.Commitment to continuous learning and improvement.Fluency in English.Excellent written and verbal communication.Flexibility to adjust work schedules as needed.
Optionally, you can add more information later (benefits, pre-screening questions, etc.)