MongoDB’s mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. We enable organizations of all sizes to easily build, scale, and run modern applications by helping them modernize legacy workloads, embrace innovation, and unleash AI. Our industry-leading developer data platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available in more than 115 regions across AWS, Google Cloud, and Microsoft Azure. Atlas allows customers to build and run applications anywhere—on premises, or across cloud providers. With offices worldwide and over 175,000 new developers signing up to use MongoDB every month, it’s no wonder that leading organizations, like Samsung and Toyota, trust MongoDB to build next-generation, AI-powered applications.

MongoDB is growing rapidly and seeking a Senior Software Engineer for the Data Platform team to be a key contributor to the critical data science and product initiatives at MongoDB. The Data Platform team focuses on building a scalable, reliable, and flexible backend system encompassing key components such as model training, deployment, instrumentation and performance tracking in order to empower critical MongoDB product and business initiatives.

As a Senior Software Engineer, you will design and build a scalable platform to effectively develop, manage and deploy in-house backend systems to help drive MongoDB’s growth as a product and as a company, while also lending your technical expertise to other engineers as a mentor and trainer. You will tackle complex platform problems with the goal of making our platform more scalable, reliable, and robust.

• You have a strong problem solving skills and take pride in the strong sense of ownership and accountability
• You have strong programming (Go, Python, Java or equivalent) skills and appetite of pursuing engineering best practices
• You have an extensive exposure to architectural patterns of large, high-scale systems with well-designed APIs, high volume data pipelines and robust monitoring
• You are a team player who can effectively communicate and collaborate with key engineering and business partners
• You are familiar with test-driven development, incremental delivery and deployment processes
• You’re passionate about developing reliable and high quality software
• You’re curious, collaborative and intellectually honest

• You have experience with working with large-scale data using distributed processing platform and query engine such as Spark, Ray and Trino
• You have an extensive experience in designing and implementing end-to-end machine learning infrastructure and productionizing machine learning models in large-scale industry settings
• You are familiar with data infrastructure and toolings such as Presto, Hive, Spark and BigQuery
• You have a working experience with containerization and orchestration platform such as Docker and Kubernetes
• You have experience with or working knowledge of cloud platforms and services
• You are familiar with operational toolings for machine learning services
• You have a security-first mindset and keen eyes on security best practices to ensure that our services adhere the security best practices

• Build production-ready services to deploy machine learning models and integrate to a variety of MongoDB systems
• Perform code reviews with peers and make recommendations on how to improve our code and software development processes
• Design machine learning system architecture that can abstract and automate critical machine learning product lifecycle including training, model management, tracking and deployment.
• Continuously optimize and tune critical infrastructure and services to ensure that the machine learning platform and services are operating efficiently
• Collaborate with other software engineers, data scientists, and key stakeholders, taking learning and leadership opportunities that will arise every single day
• Further improve the team’s testing and development processes
• Document and educate the larger team on best practices
• Help drive optimization, testing, and tooling to improve ML platform quality

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

MongoDB’s base salary range for this role is posted below. Compensation at the time of offer is unique to each candidate and based on a variety of factors such as skill set, experience, qualifications, and work location. Salary is one part of MongoDB’s total compensation and benefits package. Other benefits for eligible employees may include: equity, participation in the employee stock purchase program, flexible paid time off, 20 weeks fully-paid gender-neutral parental leave, fertility and adoption assistance, 401(k) plan, mental health counseling, access to transgender-inclusive health insurance coverage, and health benefits offerings. Please note, the base salary range listed below and the benefits in this paragraph are only applicable to U.S.-based candidates.