We are looking for a highly skilled Senior Software Engineer with expertise in Machine Learning platforms to develop, optimize, and scale cutting-edge solutions that enable seamless deployment, customization, and optimization of ML, Deep Learning (DL), and Large Language Models (LLMs). The ideal candidate will drive the design and development of backend services, manage cloud-based ML workflows, and integrate emerging technologies to elevate system performance.Key Responsibilities:Platform Development: Design, build, and maintain scalable platforms that allow customers to upload, customize, and manage ML, DL, and LLM models across cloud and on-premises environments.Backend Services: Develop robust, scalable backend services and APIs, primarily using Python, to support ML operations.CI/CD Implementation: Build and maintain CI/CD pipelines to automate integration, testing, and deployment of backend services.Data Processing Solutions: Create solutions for efficient processing of large datasets and support machine learning models across distributed cloud environments.Testing & Quality Assurance: Implement unit and integration tests using frameworks like pytest and tox, ensuring code quality and reliability.Troubleshooting: Diagnose and resolve issues related to ML jobs and cloud infrastructure, primarily using Linux/Unix environments.Containerization & Orchestration: Manage and deploy containerized applications using Docker and Kubernetes to streamline ML workflows.Cross-functional Collaboration: Work closely with data scientists and ML engineers to enhance the performance, reliability, and scalability of ML pipelines.Technology Integration: Continuously explore and integrate emerging technologies to optimize backend systems and improve scalability and efficiency.Python Expertise: Write efficient, scalable Python code, leveraging libraries such as PyTorch, scikit-learn, pandas, and numpy.Requirements:Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.6+ years of industry experience in software engineering with a focus on machine learning platforms.Proficiency in Python, with hands-on experience using libraries like PyTorch, scikit-learn, pandas, and numpy.Strong experience with containerization (e.g., Docker) and orchestration tools (e.g., Kubernetes).Solid understanding of CI/CD practices and tools.Experience with cloud platforms (AWS, GCP, Azure) and familiarity with serverless architecture.Hands-on experience with MLOps tools (e.g., MLflow, Kubeflow) to streamline ML operations.Proven expertise in troubleshooting cloud infrastructure issues using Linux/Unix.Track record of developing scalable backend services and APIs.Knowledge of test-driven development (TDD) and experience with testing frameworks like pytest and tox.Excellent problem-solving skills with the ability to collaborate across cross-functional teams.Strong communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.

Splunk is an Equal Opportunity Employer: At Splunk, we believe creating a culture of belonging isn’t just the right thing to do; it’s also the smart thing. We prioritize diversity, equity, inclusion, and belonging to ensure our employees are supported to bring their best, most authentic selves to work where they can thrive. Qualified applicants receive consideration for employment without regard to race, religion, color, national origin, ancestry, sex, gender, gender identity, gender expression, sexual orientation, marital status, age, physical or mental disability or medical condition, genetic information, veteran status, or any other consideration made unlawful by federal, state, or local laws. We consider qualified applicants with criminal histories, consistent with legal requirements.

Note:

Splunk provides flexibility and choice in the working arrangement for most roles, including remote and/or in-office roles. We have a market-based pay structure which varies by location. Please note that the base pay range is a guideline and for candidates who receive an offer, the base pay will vary based on factors such as work location as set out above, as well as the knowledge, skills and experience of the candidate. In addition to base pay, this role is eligible for incentive compensation and may be eligible for equity or long-term cash awards.

Benefits are an important part of Splunk's Total Rewards package. This role is eligible for a comprehensive, competitive benefits package which may include healthcare and retirement plans, paid time off, wellbeing expense reimbursement, and much more! Learn more about our comprehensive benefits and wellbeing offering at https://splunkbenefits.com.

Thank you for your interest in Splunk!