Job Description
Join the Future of Innovation
TechNova Solutions is at the forefront of transforming industries through cutting-edge artificial intelligence. We are seeking a Senior Machine Learning Engineer to lead our research and development team in Austin, Texas. In this pivotal role, you will architect scalable ML pipelines, develop advanced algorithms, and deploy models that power our next-generation enterprise solutions.
At TechNova, we don't just build software; we engineer the intelligence behind the world's most complex systems. You will collaborate with cross-functional teams of data scientists, product managers, and engineers to deliver impactful AI products that redefine user experiences.
Why You’ll Love It Here:
- Work with a diverse team of world-class engineers and researchers.
- Competitive compensation package and comprehensive benefits.
- Flexible remote-first culture with a hub in vibrant Austin.
- Opportunity to publish research and contribute to open-source projects.
If you are passionate about pushing the boundaries of what's possible with machine learning and eager to make a tangible impact, we want to hear from you.
Responsibilities
- Design, implement, and optimize end-to-end machine learning pipelines and data workflows.
- Research and prototype novel deep learning architectures and algorithms to solve complex business problems.
- Collaborate with product and engineering teams to integrate AI models into production environments.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
- Monitor model performance in production, ensuring accuracy, scalability, and reliability.
- Stay abreast of the latest research in the field of machine learning and apply these insights to our products.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- 5+ years of professional experience in machine learning, deep learning, or data science.
- Proficiency in Python, with strong experience in frameworks such as PyTorch, TensorFlow, or JAX.
- Strong understanding of data structures, algorithms, and software design principles.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Proven track record of deploying large-scale machine learning models into production.
- Excellent communication skills, with the ability to translate complex technical concepts to non-technical stakeholders.