Senior / Staff Machine Learning Engineer at CloseFactor Full Time

What you’ll do

As a formative Machine Learning Engineer at CloseFactor, you will play a key role in driving the strategic direction of our platform. Your expertise in machine learning will be instrumental in developing innovative strategies for shaping our AI-enabled sales solutions platform. By leveraging your strategic mindset and technical acumen, you’ll empower our clients to revolutionize their sales strategies to outperform their competition. We seek naturally curious and enthusiastic learners who can adapt to solve the range of software and business problems that emerging startups typically encounter. As an early employee at an exciting company, you will be expected to think like a strategist and execute like an entrepreneur.

• Develop and propose strategic approaches for developing ML-based recommendation products, leveraging large language models and generative AI to enhance products
• Ensure the reliability, scalability and maintainability of machine learning pipelines and infrastructure, aligning them with our strategic objectives
• Design, develop, and deploy machine learning models to solve complex business problems related to sales intelligence and analytics
• Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to define requirements and implement machine learning solutions
• Collect, preprocess, and analyze large datasets to extract valuable insights and patterns
• Optimize and fine-tune existing machine learning models to improve their accuracy, performance, and scalability
• Stay updated with the latest advancements in machine learning and related technologies, and evaluate their potential applicability to our products
• Conduct experiments and evaluate the effectiveness of different machine learning algorithms and techniques

What we’re looking for

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field
• Familiarity with large language models, NLP, or generative AI, including their capabilities, limitations, and best practices for utilization
• Experience with recommendation engines and related techniques, including those in the areas of information retrieval, vector embeddings, and the cold-start problem
• Strong background in machine learning, statistical modeling, and data analysis
• Proficiency in programming languages such as Python and knowledge of relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
• Experience in designing and implementing machine learning algorithms, including both traditional and deep learning
• Solid understanding of data preprocessing, feature engineering, and model evaluation techniques
• Familiarity with cloud platforms and technologies for deploying and scaling machine learning models (e.g. Google Cloud)
• Excellent problem-solving and analytical skills, with the ability to translate business requirements into machine learning solutions
• Effective communication skills and the ability to work collaboratively in a team-oriented environment
• High confidence, low ego