Summary: The role of Senior Software Engineer with a focus on machine learning at Cerebra Consulting Inc involves leading the integration and operationalization of ML models, particularly in the Search area. The position requires collaboration with data scientists and engineering teams, utilizing MLOps best practices to ensure effective deployment and operation of ML systems. The ideal candidate will have extensive experience with various ML platforms and a strong software engineering background. This position is remote and emphasizes teamwork and communication skills.

Key Responsibilities:

• Develop and integrate recommender systems into customer-facing products.
• Implement ML techniques such as embedding-based retrieval, reinforcement learning, and transformers.
• Collaborate with engineering teams to ensure seamless model integration.
• Drive A/B testing and iterative optimization using data-driven methodologies.
• Assess infrastructure needs for ML deployment, including CPU/GPU resources and networking requirements.
• Efficiently manage, share, and reuse machine learning features at scale using Vertex AI Feature Store.
• Implement centralized feature stores to maintain transparency and consistency across ML operations.
• Enable secure and scalable feature delivery while maintaining access control and governance.
• Work with data engineers and scientists to ensure high-quality labeled datasets.
• Ensure end-to-end integration of data pipelines to AI workflows using BigQuery and BigTable.
• Optimize data structures and storage to enhance model performance and efficiency.
• Monitor ML systems in production to identify bottlenecks and improvement opportunities.
• Implement automation strategies to improve model retraining, deployment, and performance tracking.
• Participate in support rotations and troubleshoot production ML issues as needed.

Key Skills:

• 5+ years of experience in software engineering with a focus on machine learning and MLOps.
• Expertise in Google Vertex AI, cloud ML platforms, and open-source ML tools.
• Hands-on experience with recommender systems and deep learning frameworks.
• Strong software engineering skills to integrate ML models into large-scale applications.
• Experience with A/B testing, model evaluation, and optimization techniques.
• Solid understanding of infrastructure needs for ML deployment (GPU/CPU, networking, scaling).
• Proficiency in Python, TensorFlow, PyTorch, and distributed computing frameworks.
• Strong collaboration skills to work with data scientists, engineers, and leadership teams.

Salary (Rate): undetermined

City: undetermined

Country: USA

Working Arrangements: remote

IR35 Status: outside IR35

Seniority Level: undetermined

Industry: IT