Principal Machine Learning Engineer, Splunk
Customer Data Platform
$203.2-279.4k
+ Equity
Data security & observability platform
Open for applications
Data security & observability platform
1001+ employees
Open for applications
$203.2-279.4k
+ Equity
1001+ employees
Company mission
To allow clients to focus on the business outcomes that data can deliver by helping organisations use their data to answer questions, take actions, and achieve business objectives
Role
Who you are
- Are you passionate about working on products that provide customer value?
- Do you enjoy building services that run ML pipelines with large data sets, and want to create innovative content for Splunk’s cybersecurity products?
- Do you value working in an environment where you're empowered to build a modern ML pipeline solution that helps deliver efficient solutions for Splunk’s Observability and Security products?
- If so, a role on the Splunk Customer Data Platform team could be an ideal fit for you
- Advanced degree (Master’s or Ph.D.) in Computer Science, Data Science, or a related field
- 10+ years of experience in applied machine learning or related fields
- Strong programming skills in languages such as Python, Java, C++, or Scala
- Expertise in data engineering, iterative ML model development using automated ML pipelines, distributed computing, cloud platforms (e.g., AWS, GCP), and ML frameworks (e.g., SageMaker, EMR Serverless, Glue, TensorFlow, PyTorch)
- Strong problem-solving capabilities with analytical thinking
- Leadership skills to manage teams and drive critical initiatives
- Excellent communication skills for multi-functional collaboration
- Project management expertise to supervise timelines and resource allocation effective
What the job involves
- We are seeking a senior engineer with ML & AI expertise, preferably with experience in ML model development, training and deployment flows to lead Splunk's Customer Data Platform delivery
- Your mission is to build a modern ML development pipeline, complete with curated datasets to fuel diverse content requirements, support training and execution runtimes that closely emulate live deployments. Splunk's customer data platform powers our product offerings in the Observability, SIEM and SOAR space, with an aim to deliver high efficacy content and workflows trained and optimized with curated pseudo-anonymized datasets, originating from customer environments
- Lead the development of end-to-end ML systems, including data preprocessing, model training, evaluation, and deployment in production environments
- Find opportunities for improvement with our ML-Ops processes and practices and promote these successfully within the team
- Architect robust ML pipelines and scalable infrastructure using cloud platforms and distributed computing technologies
- Build frameworks for curating training data, model evaluation, and monitoring deployed systems
- Champion cross-team collaborations and drive the adoption of AI/ML tools across organizations. Ensure ML pipelines align with DevOps and ML-Ops industry friendly standard practices
- Design, implement, and optimize ML algorithms and models to deliver customer value and build training datasets using large volumes of real production data
- Stay updated on advancements in ML techniques (e.g., LLMs, personalization algorithms) to explore innovative applications for business needs
- Innovate by prototyping new ideas and scaling successful solutions into production systems
- Work with product managers to translate business requirements into technical solutions
- Act as a liaison between technical teams and non-technical counterparts to communicate complex insights effectively
- Ensure models meet data governance and privacy regulations and compliance rules (GDPR, HIPAA, CCPA etc)
- Ensure fairness, transparency, and ethical considerations in ML models by addressing biases in algorithm
Our take
Splunk was founded to produce software for searching and analysing machine-generated data for clients. The platform provides live data insights and is an attractive option due to its flexibility, scalability and ability to process real time data.
The company has evolved significantly since being founded, implementing developments in augmented reality, machine learning and mobile technology. Further, the company's transition to the cloud has allowed it to provide new offerings, and proved its ability to move with market trends.
Acquired by Cisco in 2024, Splunk now benefits from Cisco's user protection, breach protection and threat intelligence capabilities. The company will continue to deliver its security products, and also has plans to enhance its portfolio moving forwards.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 3 rounds)
Sep 2007
$25m
SERIES C
Jan 2006
$10m
SERIES B
Total funding: $40m
Company benefits
- Paid parental leave
- Work from home opportunities
- Health Care and Insurance
- Paid Time Off
- Education reimbursement
- Electric car charging stations
- Employee Assistance Program (EAP)
- Stocked kitchens
- Gym discounts/onsite fitness centers
- Pet insurance discount
- Student loan resources
- Cool workspace with collaborative environments
- 529 College Savings Plan
Company HQ
South Beach, San Francisco, CA
Leadership
Gary Steele
(EVP & GM of Splunk at Cisco, not founder)Was CEO and President of Splunk before it became a Cisco company. Previously CEO at Proofpoint and Portera, VP at Sybase, and Market Development Manager at Sun Microsystems.
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