Job Description
Are you ready to shape the future of AI? Apex Data Systems is seeking a visionary Senior Machine Learning Engineer to join our elite team in the heart of San Francisco. We are on a mission to revolutionize how businesses leverage predictive analytics.
In this role, you will not just write code; you will architect solutions that drive real-world impact. You will work alongside world-class data scientists and engineers to build proprietary algorithms that power our core products. If you thrive in a fast-paced, innovative environment and love turning complex data into actionable business intelligence, we want to hear from you.
Why join Apex Data Systems?
- Competitive salary and equity package.
- Comprehensive health benefits and 401(k) matching.
- Flexible remote-first policy with a vibrant office culture.
Responsibilities
- Model Development: Design, train, and deploy scalable machine learning models using Python and deep learning frameworks.
- Data Engineering: Build and optimize robust data pipelines to ensure high-quality data ingestion and processing.
- Collaboration: Partner with product managers and engineering teams to identify high-impact business opportunities and translate them into technical solutions.
- Optimization: Conduct rigorous A/B testing, model validation, and performance tuning to ensure production-grade reliability.
- Research: Stay abreast of the latest advancements in AI research and apply cutting-edge techniques to our product suite.
Qualifications
- Education: Master’s or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
- Experience: 3+ years of professional experience in Machine Learning engineering or a similar data science role.
- Technical Skills: Strong proficiency in Python, SQL, and deep learning frameworks such as TensorFlow or PyTorch.
- Communication: Excellent verbal and written communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
- Problem Solving: Proven track record of solving ambiguous problems and delivering scalable solutions under tight deadlines.