Staff Machine Learning Engineer

Job Description What You'll do: - Apply leading Models to solve business problems - Use models from GPT-*to LLama-*to solve wide range of business problems from sales tech, employee productivity, coding and automation - Build RAG frameworks - Build Langchain modules - Model Development and Implementation: - Design, develop, and deploy machine learning models to solve complex problems and improve user experiences, operational efficiency, or system performance. - Utilize a variety of data sources, types, and structures to extract actionable insights through predictive analytics and data mining techniques. - Research and Innovation: - Stay abreast of the latest developments in the field of machine learning and artificial intelligence. Evaluate emerging trends and technologies for potential adoption to maintain and expand competitive advantage. - Lead research initiatives that test new algorithms, evaluate new methodologies, and explore innovative uses of data that can lead to scalable solutions. - Team Leadership and Development: - Lead and mentor a team of machine learning engineers and data scientists. Ensure the continuous professional growth of team members through clear goal-setting, regular feedback, and development opportunities. - Foster a collaborative and inclusive team environment that encourages innovation and iterative learning. - Cross-Functional Collaboration: - Work closely with product management, software engineering, and data engineering teams to integrate machine learning models into larger software systems and product offerings. - Partner with stakeholders across the organization to understand business needs and translate them into technical requirements and actionable machine learning projects. - Project Management: - Oversee the full project lifecycle for multiple machine learning initiatives, from ideation and data collection to model development and deployment. - Manage resources, timelines, and risks effectively, ensuring that projects meet their objectives and are delivered on schedule. - Performance Monitoring and Model Optimization: - Continuously monitor the performance of deployed models, identifying opportunities for improvement and optimization. - Implement robust testing and validation strategies to ensure model accuracy and reliability over time. - What You'll Need: - Experience in applying Gen-AI/LLM in production - Managed at least a team 4+ engineers for end-to-end deliverables, for more than 2 years - Education: Bachelor's degree in Computer Science, Engineering, or a closely related field. Advanced degrees (Master's or PhD) in fields that emphasize software engineering or machine learning are preferred. - Professional Experience: At least 8 years of experience in software development with a proven track record in both software engineering and research or applied machine learning projects. - Technical Expertise: - Expertise in programming using languages such as Python, Java, C++, or Scala. - Proficient with modern software engineering tools and methodologies (e.g., version control, CI/CD, agile development practices). - Extensive experience with machine learning libraries and frameworks like TensorFlow, PyTorch, or Keras. Data Proficiency: - Strong capabilities in handling large datasets, with skills in SQL, NoSQL databases, data modeling, and ETL processes. - Experience designing and implementing systems that collect, manage, and convert raw data into actionable insights through machine learning models. - Machine Learning Application Experience: - Solid foundation in applying machine learning algorithms to real-world problems, optimizing algorithms for scalability and performance. - Hands-on experience in building, scaling, and maintaining production-level machine learning models.