Senior Software Engineer, AI/ML Platform

Job Description

Senior Software Engineer, AI/ML Platform

Innovate AI Solutions Inc. is a pioneering technology company at the forefront of artificial intelligence and machine learning innovation. We are dedicated to building robust, scalable, and intelligent platforms that empower businesses to transform their operations and deliver cutting-edge experiences. Our culture thrives on curiosity, collaboration, and a relentless pursuit of excellence, where every team member is encouraged to contribute meaningfully to our collective success.

About the Role

As a Senior Software Engineer, AI/ML Platform, you will play a pivotal role in designing, developing, and maintaining the core infrastructure that powers our advanced AI and Machine Learning models. You will be instrumental in building highly scalable, reliable, and efficient systems that enable data scientists and machine learning engineers to rapidly develop, train, deploy, and monitor models in production. This role requires a strong blend of software engineering expertise, a deep understanding of MLOps principles, and a passion for building robust platforms that unlock the full potential of AI.

Key Responsibilities

• Platform Architecture & Design: Lead the architectural design and implementation of core components for our AI/ML platform, focusing on scalability, reliability, security, and performance.
• MLOps Development: Build and optimize automated CI/CD pipelines for ML models, ensuring seamless integration, continuous training, testing, and deployment processes from experimentation to production.
• Feature Store Development: Design and implement a robust feature store to manage and serve machine learning features consistently across training and inference, ensuring data quality and reducing engineering overhead.
• Model Serving & Inference: Develop highly performant and scalable model serving infrastructure (e.g., REST APIs, gRPC services) capable of handling high-throughput, low-latency real-time inference requests.
• Monitoring & Observability: Implement comprehensive monitoring, logging, and alerting systems for ML models and infrastructure to detect anomalies, track performance, and ensure operational stability in production.
• Tooling & Automation: Create developer-friendly tools, libraries, and SDKs that streamline the workflow for data scientists and ML engineers, enhancing productivity and standardizing best practices.
• Collaboration & Mentorship: Work closely with data scientists, ML engineers, and other engineering teams to understand requirements, provide technical guidance, and champion best practices in MLOps and platform engineering.
• Performance Optimization: Identify and resolve performance bottlenecks in the ML pipeline, from data ingestion to model inference, leveraging cloud-native technologies and distributed systems.

Required Skills & Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related quantitative field.
• Experience: 5+ years of professional software development experience, with at least 2-3 years specifically focused on building AI/ML platforms, MLOps, or data engineering for ML.
• Programming Proficiency: Expert-level proficiency in Python; strong command of object-oriented programming, data structures, and algorithms. Experience with Go, Java, or Scala is a plus.
• Cloud Platforms: Extensive experience with at least one major cloud provider (AWS, GCP, or Azure), including knowledge of relevant services (e.g., S3/GCS, EC2/GCE, Sagemaker/Vertex AI, Kubernetes, Lambda/Cloud Functions).
• MLOps Tools: Hands-on experience with MLOps frameworks and tools such as MLflow, Kubeflow, Airflow, ZenML, TFX, or similar.
• Containerization & Orchestration: Strong understanding and practical experience with Docker and Kubernetes for deploying and managing microservices and ML workloads.
• Distributed Systems: Experience designing and implementing scalable and fault-tolerant distributed systems.
• Data Stores: Proficiency with various database technologies (SQL, NoSQL, data warehouses like Snowflake/BigQuery) and stream processing frameworks (Kafka, Kinesis).
• Communication: Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.

Preferred Skills & Qualifications

• Deep Learning Frameworks: Familiarity with deep learning frameworks such as TensorFlow, PyTorch, or JAX.
• ML Algorithms: Basic understanding of various machine learning algorithms and their lifecycle.
• Infrastructure as Code: Experience with Infrastructure as Code (IaC) tools like Terraform or CloudFormation.
• Open Source Contributions: Contributions to open-source MLOps or data engineering projects.
• Security: Knowledge of security best practices for cloud environments and ML platforms.

What We Offer

• Competitive Compensation: A comprehensive salary and equity package that recognizes your expertise and contributions.
• Comprehensive Benefits: Generous health, dental, and vision insurance, 401(k) with company matching, and life insurance.
• Professional Development: Opportunities for continuous learning, attending conferences, and advancing your career in a rapidly evolving field.
• Dynamic Work Environment: A collaborative, innovative, and inclusive culture where your ideas are valued and your impact is visible.
• Work-Life Balance: Flexible working hours, generous paid time off, and options for remote or hybrid work arrangements.
• Cutting-Edge Technology: Work with the latest tools and technologies in AI/ML and cloud computing.

Apply Now

If you are a passionate and experienced engineer eager to build the future of AI infrastructure and thrive in a fast-paced, innovative environment, we encourage you to apply!

Please submit your resume along with a cover letter detailing your relevant experience, your approach to MLOps challenges, and why you believe you are the ideal candidate for this role at Innovate AI Solutions Inc.