Senior Full-Stack Engineer (Specialized in Machine Learning)
Prachas Technologies ·Austin, TXClosing in
Term:Full timeWork:Onsite
Type:EmployeeContract
Join Unnanu and be part of a forward-thinking team dedicated to reshaping the future of AI recruitment and data governance. Apply now to embark on an exciting journey of innovation and impact.
Company Overview:
Unnanu is a pioneering company at the forefront of integrating machine learning technologies into the recruiting and AI data governance sectors. We are committed to leveraging the power of machine learning to drive actionable insights and enhance decision-making processes in recruitment and data governance. We are seeking a talented Full-Stack Engineer with a specialization in Machine Learning to join our innovative team. If you are passionate about building intelligent applications that redefine industry standards, we encourage you to apply.
Position Overview:
As a Full-Stack Engineer specialized in Machine Learning at Unnanu, you will play a pivotal role in developing end-to-end solutions that seamlessly integrate machine learning models into our web applications. You will collaborate closely with our product development, data science, and AI data governance teams to implement and deploy machine learning algorithms that optimize recruitment processes and enhance data governance strategies. The ideal candidate is a self-driven problem solver with a strong command of both front-end and back-end technologies, along with expertise in machine learning concepts and frameworks.
Responsibilities:
- Design, develop, and maintain scalable web applications that incorporate machine learning models using modern front-end and back-end technologies.
- Collaborate with data scientists and AI data governance specialists to understand requirements, implement machine learning algorithms, and deploy predictive models into production environments.
- Implement RESTful APIs to facilitate communication between front-end interfaces and machine learning services.
- Design and optimize databases to store and retrieve large volumes of structured and unstructured data for training and inference.
- Develop intuitive user interfaces that visualize insights generated by machine learning models and empower users to make data-driven decisions.
- Optimize application performance and ensure high availability, reliability, and scalability.
- Conduct code reviews, write unit tests, and debug issues to maintain code quality and stability.
- Stay updated on emerging technologies and best practices in machine learning, web development, and cloud computing.
Qualifications:
- Bachelor's degree in Computer Science, Engineering, or related field. Advanced degree (MS/Ph.D.) in Computer Science or Machine Learning is a plus.
- Proven experience as a Full-Stack Engineer or similar role, with a focus on integrating machine learning models into web applications.
- Strong proficiency in front-end technologies such as HTML5, CSS3, JavaScript (e.g., React, Vue.js) and back-end technologies such as Node.js, Express.js.
- In-depth understanding of machine learning concepts, algorithms, and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform for deploying and managing machine learning services.
- Proficiency in database technologies (e.g., SQL, NoSQL) for storing and querying structured and unstructured data.
- Familiarity with version control systems (e.g., Git) and CI/CD pipelines.
- Strong problem-solving skills and attention to detail.
- Excellent communication and teamwork abilities.
Preferred Qualifications:
- Experience with containerization and orchestration tools (e.g., Docker, Kubernetes) for deploying and scaling machine learning applications.
- Knowledge of natural language processing (NLP) or computer vision (CV) techniques and libraries.
- Familiarity with reinforcement learning or other advanced machine learning paradigms.
- Contributions to open-source machine learning projects or active participation in developer communities focused on AI and machine learning.
Benefits:
- Competitive salary package with performance-based incentives.
- Flexible work schedule and remote work options.
- Opportunities for professional development and career advancement in a dynamic and rapidly growing field.
- Collaborative and inclusive work environment with a focus on innovation and continuous learning.