Senior Software Engineer, AI/ML Platform

Job Description

Senior Software Engineer, AI/ML Platform

Are you a passionate and experienced Software Engineer looking to make a significant impact in the rapidly evolving field of Artificial Intelligence and Machine Learning? Join our innovative team at [Company Name] and help us build the next generation of AI/ML platforms that power our groundbreaking products and services.

About [Company Name]

[Company Name] is a leading technology company at the forefront of innovation, dedicated to solving complex problems and creating a better future through intelligent solutions. We foster a culture of curiosity, collaboration, and continuous learning, empowering our employees to push boundaries and achieve their full potential. Our mission is to [briefly state company mission, e.g., “revolutionize how businesses interact with data” or “empower individuals through cutting-edge technology”].

Job Summary

As a Senior Software Engineer specializing in AI/ML Platforms, you will be a pivotal member of our engineering team, responsible for designing, developing, and maintaining scalable, high-performance infrastructure and tools that enable our data scientists and ML engineers to build, train, and deploy machine learning models efficiently. You will work on critical components of our ML lifecycle, from data ingestion and feature engineering to model serving and monitoring. This role requires strong software engineering fundamentals, a deep understanding of cloud platforms, and practical experience with various AI/ML technologies and frameworks.

Key Responsibilities

• Platform Design & Development: Architect, design, and implement robust, scalable, and secure ML platform components, including MLOps pipelines, feature stores, model registries, and serving infrastructure.
• Tooling & Automation: Develop internal tools, libraries, and automation scripts to streamline the end-to-end ML lifecycle, improving productivity and reducing manual effort for ML teams.
• Performance & Scalability: Optimize platform components for performance, reliability, and cost-efficiency on cloud infrastructure (e.g., AWS, GCP, Azure), ensuring our ML models can scale to handle large datasets and high inference traffic.
• Collaboration & Support: Work closely with data scientists, ML engineers, and product teams to understand their needs, provide technical guidance, and integrate new capabilities into the platform.
• Best Practices & Governance: Advocate for and implement software engineering best practices, including code reviews, testing, documentation, and continuous integration/continuous deployment (CI/CD) for ML systems.
• Innovation & Research: Stay abreast of the latest advancements in AI/ML, cloud computing, and MLOps, evaluating new technologies and contributing to the strategic direction of our platform.
• Mentorship: Provide technical leadership and mentorship to more junior engineers, fostering a culture of technical excellence and growth within the team.

Qualifications

Required Qualifications:

• Experience: 5+ years of professional software development experience, with at least 2-3 years focused on building and scaling AI/ML infrastructure or related data platforms.
• Programming Languages: Strong proficiency in Python and at least one other compiled language (e.g., Java, Go, Scala, C++).
• Cloud Platforms: Extensive experience with at least one major cloud provider (AWS, GCP, Azure), including familiarity with their compute, storage, networking, and data services.
• ML Frameworks & Libraries: Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, and familiarity with distributed computing frameworks (e.g., Spark).
• Data Engineering: Solid understanding of data structures, algorithms, and experience with data processing technologies (e.g., Apache Kafka, Apache Flink, Apache Spark, SQL/NoSQL databases).
• MLOps Principles: Demonstrated understanding and practical application of MLOps principles, including CI/CD for ML, model versioning, monitoring, and lineage.
• System Design: Proven ability to design and implement complex, scalable, and fault-tolerant distributed systems.
• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.

Preferred Qualifications:

• Containerization & Orchestration: Experience with Docker, Kubernetes, and serverless technologies.
• Feature Stores: Familiarity with feature store concepts and tools (e.g., Feast, Tecton).
• ML Platform Tools: Experience with managed ML services (e.g., AWS SageMaker, GCP Vertex AI, Azure ML) or open-source MLOps platforms (e.g., MLflow, Kubeflow).
• Big Data Technologies: Experience with data warehousing solutions (e.g., Snowflake, BigQuery, Redshift) and data lake architectures.
• Communication: Excellent verbal and written communication skills, with the ability to articulate complex technical concepts to diverse audiences.

What We Offer

• Competitive Compensation: Attractive salary package, including equity options, commensurate with experience and impact.
• Comprehensive Benefits: Health, dental, and vision insurance for you and your family, 401(k) matching, and generous paid time off.
• Professional Development: Opportunities for continuous learning, conferences, workshops, and internal training programs to help you grow your skills and career.
• Innovative Environment: Work on challenging and cutting-edge problems with a team of brilliant and passionate engineers and scientists.
• Impactful Work: Contribute directly to products and services that have a tangible impact on our users and the industry.
• Flexible Work: Hybrid or remote-friendly work options to support work-life balance.
• Culture: A vibrant, inclusive, and collaborative work environment where your ideas are valued.

How to Apply

If you are excited about building the future of AI/ML and meet the qualifications outlined above, we encourage you to apply! Please submit your resume and a cover letter detailing your relevant experience and why you are interested in this role through our careers portal at [Link to Careers Page or Email Address].

Equal Opportunity Employer

[Company Name] is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.