Lead Artificial Intelligence Engineer

About the job

As a Lead Artificial Intelligence Engineer at Leapfrog Technology, you will be at the forefront of shaping the future of data-driven solutions. You'll lead a talented team, drive the development of innovative AI projects, and work collaboratively across functions to turn complex business challenges into actionable insights. Key Responsibilities: ● Leadership Excellence: Lead and inspire a team of AI Engineers and Data Scientists, fostering a culture of innovation, collaboration, and continuous growth. ● End-to-End Ownership: Take full ownership of the AI project lifecycle, from ideation and design to development, deployment, and maintenance. ● Technological Innovation: Explore and assess emerging technologies to enhance the performance, maintainability, and reliability of AI systems. ● Engineering Best Practices: Apply robust software engineering practices to AI, including CI/CD pipelines, automation, and quality assurance. ● Architectural Leadership: Collaborate with technology experts to make informed architectural decisions, and ensure thorough technical documentation. ● Risk Mitigation: Proactively identify and address project risks, conduct root cause analysis, and implement preventive measures. ● Cross-functional Collaboration: Engage closely with cross-functional teams, including business stakeholders, product managers, software engineers, and data engineers, to deliver impactful data-driven solutions. ● Continuous Learning: Stay at the cutting edge of data science, ML, and AI developments, and leverage emerging technologies to solve complex business problems. ● Mentorship and Growth: Coach and motivate team members, identify training needs, and foster their professional development. ● Organizational Excellence: Actively uphold and promote the company's culture, processes, and standards to ensure consistent excellence in our work. Education and Experience: • A degree (Masters preferred) in Computer Science, Engineering, Artificial Intelligence, Data Science, Applied Mathematics, or related fields. • Minimum 6+ years of hands-on experience in AI/ML or Data Science, preferably in real industry settings, with a track record of building data products that have positively impacted customer satisfaction and revenue growth. Technical Skills: • Proficiency in a wide range of Machine Learning techniques and algorithms, with the ability to apply advanced analytics methods, including Bayesian statistics, clustering, text analysis, time series analysis, and neural networks on large-scale datasets. • Expertise in at least one specialized area of application, such as Computer Vision or Natural Language Processing (NLP). (NLP Expertise preferred) • Strong programming skills in Python, including expertise in the data ecosystem (Numpy, Scipy, Pandas, etc.) or equivalent skills in languages like R, Java, Scala, or Julia, with a focus on producing production-quality code. • Hands-on experience with popular ML frameworks like Scikit-Learn, PyTorch, or TensorFlow. • Expertise with Generative AI and Large Language Models (LLMs) along with their implementation in real-life applications. • Experience building end-to-end ML systems (MLOps). • Experience in deploying code in web frameworks such as Flask, FastAPI or Django. • Experience working in a cloud environment like AWS, Azure, or GCP for ML work. • Good grasp of SQL/NoSQL databases and scripting skills, particularly within analytics platforms and data warehouses. • Good grasp of software engineering concepts (SDLC, Version Control, CI/CD, Containerization, Scalability and so on), programming concepts, and tools/platforms like Git and Docker. • Bonus: Experience with Big Data technologies such as Apache Spark, Kafka, Kinesis, and cloud-based ML platforms like AWS SageMaker or GCP ML Engine. • Bonus: Experience with data visualization and dashboard tools like Tableau or Power BI. Soft Skills: • Highly motivated, self-driven, entrepreneurial mindset, and capable of solving complex analytical problems under high-pressure situations. • Ability to work with cross-functional and cross-regional teams. • Ability to lead a team of Data/AI professionals and work with senior management, technological experts, and the product team. • Excellent written and verbal communication skills, comfortable with client communication. • Good leadership skills - ability to motivate and mentor team members, ability to plan and make sound decisions, ability to negotiate tactfully with the client and team. • Results-oriented, customer-focused with a passion for resolving tough technical and operational challenges. • Possess excellent analytical and problem-solving abilities. • Good documentation skills. • Experienced with Agile methodologies like Scrum/Kanban.

Requirements

• Leadership
• Machine Learning
• Data Science
• NLP
• Python

Preferred Technologies

• Leadership
• Machine Learning
• Data Science
• NLP
• Python