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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in backend engineering with a strong focus on Go and Python, alongside experience in building and maintaining high-load systems. Proficient in CI/CD processes, observability practices, and collaboration with cross-functional teams in the ML lifecycle.
Highest-signal resume keywords
Go ProgrammingPython ProgrammingSQL Database DesignCI/CD Pipeline ManagementAWS or GCP Services
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Backend EngineeringHigh-Load SystemsData ProcessingObservability DesignInfrastructure as CodeModel Performance MetricsTechnical ResearchDeployment ToolingService MonitoringData Capture
Soft Skills
Mentoring EngineersExplaining Trade-OffsCollaboration
Tools & Technologies
DockerKubernetesTerraformPrometheusGrafanaELK StackRedisKafkaRabbitMQGit
Industry Keywords
Machine Learning LifecycleMLOpsData PreparationModel ServingConcept Drift
Tech Stack
Tools & technologiesAirflowAWSDNSDockerGoogle Cloud PlatformGrafanaGRPCKafkaKubernetesLinuxPrometheusPythonPyTorchRabbitMQRedisScikit-LearnSQLTCP/IPTensorflowTerraformGo
About the role
Key responsibilities & impact- Design, build, and run backend services and internal tooling for the ML platform using Go and Python.
- Own services in production, including delivery, monitoring, and on-call responsibilities.
- Conduct technical research and design new platform features while documenting trade-offs.
- Build and extend deployment tooling and SDKs for model serving, autoscaling, and data capture.
- Integrate ML services with the wider backend through reliable synchronous and asynchronous communication.
- Support the ML delivery cycle with data scientists and ML engineers, including model and pipeline CI/CD, monitoring, and performance metrics.
- Build end-to-end observability covering metrics, logs, dashboards, tracing, alerting, and runbooks.
- Write infrastructure as code with Terraform and Terragrunt and deliver it through reviewed pull requests.
- Participate in code and design reviews, mentor engineers, and review AI-generated changes to the same standard as human-written changes.
- Collaborate with data scientists, ML engineers, software engineers, and data engineers.
Requirements
What you’ll need- 5+ years of commercial backend engineering, including high-load systems.
- Strong Go, including advanced features used in production.
- Solid Python for data processing and service code.
- Strong SQL, including schema design, indexes, query optimization, replication, and partitioning.
- Experience with Redis or similar key-value stores.
- Experience with HTTP, gRPC, Kafka, or RabbitMQ, focusing on reliability.
- Docker, CI/CD pipelines, and working Kubernetes knowledge.
- Experience with AWS or GCP core services, including compute, storage, networking, and IAM.
- Understanding of the ML lifecycle, data preparation, model performance metrics, non-functional requirements, and concept drift.
- Familiarity with scikit-learn and PyTorch/TensorFlow.
- Experience designing and running observability using metrics, logging, dashboards, tracing, Prometheus, Grafana, ELK, or similar.
- Git workflows, code review, Linux command line, and networking basics including TCP/IP, DNS, VPC, and load balancers.
- Ability to explain trade-offs clearly to data scientists, product owners, and on-call engineers.
- Nice to have: MLOps tooling experience with Databricks, SageMaker, Kubeflow, MLflow, or Airflow; GPU or LLM inference experience; AI coding agent experience; emerging markets experience; Infrastructure-as-Code experience.
Benefits
Comp & perks- Real scale and real constraints: models serving a global fleet, GPU budgets that matter, LLM workloads reaching production.
- A strong backend engineer can grow into the MLOps domain here. We will teach you the platform side; you bring the engineering craft.
- Help us challenge injustice by creating fair choices for millions of people across 48 countries.
- Develop your professional skills with access to mentoring, career consulting, and learning programs.
- Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program.
- Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects.
- Work alongside people who take initiative, speak openly, and challenge themselves to grow.
- Improve your language skills through co-financed courses and internal speaking clubs.
- Final benefits may vary depending on the location.