Company Description
PrimeAI is a company that specializes in providing production machine learning at scale. Our AI/machine learning engines can be seamlessly deployed to companies through our cloud microservices architecture. We focus on driving top-line and bottom-line improvement for businesses through forecasting, prediction, and optimization.
With a strong emphasis on private equity, our light-touch machine learning architecture is designed to meet the time-constrained nature of PE investments. We connect to existing portfolio tech stacks to drive significant EBITDA gains. Our PE Playbook Software for AI/ML serves as a portfolio-wide interface for deploying machine learning engines into portfolio companies for specific use cases, allowing for seamless deployment, tracking, and measurement of benefits across the entire portfolio.
Job Description: We are seeking a talented and motivated Machine Learning Engineer to join our team. As an ML Engineer at PrimeAI, you will play a crucial role in developing and deploying our API-based AI products. You will work closely with cross-functional teams including software, data science, and cloud infrastructure to design, build, and deploy scalable AI solutions that address the unique needs of our clients. This is a role that spans software engineering and AI/ML/Data Science and requires a combination of strong programming skills and familiarity with ML algorithms.
Responsibilities:
- Develop and optimize Python-based code for testing and deploying machine learning models.
- Collaborate with software engineers to integrate machine learning algorithms into our API-based AI engines.
- Deploy software on cloud platforms such as AWS (preferred), Azure, or Google Cloud Platform.
- Work closely with product managers and stakeholders to understand requirements and define project goals.
- Conduct experiments, analyze data, and iterate on machine learning models to improve performance and accuracy.
- Stay up-to-date with the latest advancements in AI/ML research and technologies through publications, conferences, etc.
Requirements:
- Master's or PhD in Computer Science, Engineering, Mathematics, or a related field.
- Proven experience in developing machine learning models and algorithms using Python and popular libraries such as PyTorch, LangChain, scikit-learn, etc.
- Strong understanding of machine learning concepts, algorithms, and techniques (e.g., supervised learning, unsupervised learning, deep learning).
- Experience with cloud platforms and knowledge of deploying software on AWS (preferred), Azure, or Google Cloud Platform.
- Strong software skills including CI/CD pipelines, infrastructure as code, object-oriented paradigms, etc.
- Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.
- Strong communication skills and ability to effectively communicate technical concepts to non-technical stakeholders.
- Comfortable working in a rapidly changing environment