Senior Software Engineer - AI/ML Engineering Platform

Are you looking to work for an innovative and exciting company from Silicon Valley or New York, 100% remotely?

We are looking for a highly skilled and experienced Senior Software Engineer – AI/ML Engineering Platform to join an innovative engineering team.

We are seeking a motivated and technically strong engineer with a solid background in backend systems, ML infrastructure, search, data pipelines, and scalable distributed systems. The ideal candidate will have hands-on experience building production-grade platforms that support search, retrieval, ranking, recommendations, personalization, and AI/ML-driven features.

The salary range is 5,000 USD to 6,000 USD per month, depending on the candidate’s experience and seniority.

Candidates from Latin America may be considered. Candidates in a time zone outside of the western hemisphere will NOT be considered. The role is 100% remote.

ALL RESUMES MUST BE SUBMITTED IN ENGLISH

Responsibilities:

• Design and build scalable backend systems and distributed platforms compatible with AI/ML infrastructure.
• Build and manage ML pipelines using tools such as Vertex AI Pipelines for training, evaluation, and deployment.
• Develop and maintain data pipelines that support feature generation, model training, and analytics workflows.
• Own vector generation, storage, and retrieval workflows using vector databases such as Milvus or Pinecone.
• Implement model serving solutions using KServe and build low-latency APIs using FastAPI.
• Build observability and monitoring for models, pipelines, and production systems.
• Track model performance, drift, failures, and data quality issues.

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• Collaborate with Data Science, Product, Platform, and Engineering teams to define and deliver ML-driven features.
• Debug production issues across indexing, retrieval, ranking, and serving layers.
• Improve reliability, scalability, and performance of backend and ML systems.
• Create and maintain clear documentation for pipelines, models, APIs, and system design.
• Contribute to engineering standards, code quality, and best practices across Python-based services and ML systems.
• Stay current with advancements in AI, ML infrastructure, MLOps, search, ranking, and recommendation systems.

Requirements:

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 6+ years of experience building scalable backend systems and services.
• 5+ years of experience developing software using object-oriented languages.
• Strong proficiency in Python.
• Experience with backend and API development using Python, FastAPI, Node.js, and TypeScript.
• Experience with Elasticsearch for search, indexing, relevance tuning, retrieval, and query optimization.
• Experience with event-driven architecture and streaming systems using Apache Kafka.

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• Experience designing and building data pipelines using tools such as Apache Beam and Apache Airflow.
• Familiarity with vector search and embeddings infrastructure using Milvus, Pinecone, or similar vector databases.
• Experience with cloud platforms such as AWS and GCP.
• Experience with Docker and Kubernetes.
• Experience with observability and monitoring tools such as Grafana, Kibana, and APM.
• Strong understanding of Git and version control platforms such as Bitbucket.
• Experience designing and consuming RESTful and GraphQL APIs.
• Understanding of API versioning, documentation, OAuth, JWT, and security best practices.
• Comfortable deploying, versioning, and monitoring models in production.
• Familiarity with experimentation and analytics tools such as Jupyter Notebook and Apache Spark.
• Good understanding of machine learning concepts, including supervised learning, unsupervised learning, deep learning, NLP, ranking, retrieval, and personalization.
• Ability to review code, provide clear feedback, and improve overall engineering quality.
• Strong problem-solving skills with a data-driven approach.
• Strong communication skills and ability to explain technical concepts clearly to both technical and non-technical stakeholders.
• Fluent in English. You must be able to have a fluent professional conversation in English.