Senior Software Engineer – Backend, Machine Learning

This is a fully remote position, open to applicants in United States.

📋 Description

• Responsible for the development, testing, deployment, and maintenance of software.

• Approaches new challenges and opportunities with a sense of urgency, enthusiasm, and high energy.

• Creates test suites (functional, destructive, etc.) to facilitate successful and rapid code deployment to production.

• Engages in collaboration with team members within agile processes.

• Innovates new and improved strategies for the organization’s success.

• Works alongside the Product Team to ensure that user stories are valuable, developer-ready, clear, and testable.

• Delivers multi-channel communications that clearly address the unique needs of diverse audiences.

• Aids in the development of junior engineers by offering guidance on contemporary software development frameworks.

⛳️ Requirements

• 3-5 years of relevant experience.

• Proficient in at least one of the following: Java, Scala, Python.

• Experience with microservices, including REST APIs, gRPC, and event-driven architecture (Pub/Sub, Cloud Tasks).

• Knowledge of system design, including distributed systems, scalability, fault tolerance, and API gateway patterns.

• Familiarity with GCP Core services such as Compute Engine, GKE, Cloud Run, Cloud Functions, and IAM.

• Advanced SQL skills with BigQuery, including partitioning, clustering, and cost optimization.

• Experience with data pipelines using Dataflow (Apache Beam) and Dataproc (Spark) for both batch and streaming data.

• Knowledge of storage solutions like Bigtable, Cloud Storage, and Firestore.

• Experience with orchestration tools such as Cloud Composer (Airflow) and Workflows.

• Familiarity with Vertex AI, including model training, hyperparameter tuning, pipelines, and model registry.

• Experience with frameworks like TensorFlow, PyTorch, and scikit-learn.

• Knowledge of MLOps practices, including model serving (Vertex AI Endpoints), monitoring, and retraining pipelines.

• Familiarity with Feature Stores, specifically Vertex AI Feature Store.

• Experience with Search ML techniques such as ranking, relevance tuning, and embeddings (a plus).

• Understanding of AI & LLM Gemini, including Gemini API, Gemini Pro, and multimodal usage.

• Familiarity with Vertex AI Generative AI, including Model Garden, grounding, and tuning.

• Knowledge of Retrieval Augmented Generation (RAG) and Vector Search (Vertex AI Vector Search).

• Experience with Agentic AI frameworks, focusing on multi-agent frameworks, tool usage, and autonomous workflows.

🏝️ Benefits

• Health insurance.

• 401(k) matching.

• Paid time off.

• Flexible work hours.

• Opportunities for professional development.