Sr ML Software Development Engineer (AI)

Location: Pleasanton, California, United States; Flex hybrid work with at least 50% of each quarter spent in the office or in the field with customers, prospects, or partners.

Annual base salary: $192,000–$288,000 USD in the primary location; $163,000–$288,000 USD in additional US locations.

Company

hirify.global is a Fortune 500 company and AI platform for managing people, money, and agents.

What you will do

• Architect, deploy, and operate end-to-end ML pipelines covering distributed ingestion, feature engineering, training, evaluation, and production deployment.
• Design LLM-driven recommendation features, agentic workflows, and next-best-action models.
• Build and optimize low-latency inference and scoring microservices for high-concurrency, multi-tenant environments with sub-second response times.
• Integrate OpenTelemetry, LangChain, and LangSmith for model, prompt, response, and agent-execution observability.
• Use ClickHouse, Apache Iceberg, Spark, and related data platforms for feature retrieval and analytics.
• Partner with Product, Data Engineering, SRE, and Legal/Compliance; mentor engineers and drive technical and governance alignment.

Requirements

• 8+ years in ML research, development, and implementation of advanced models or techniques, including 4+ years building, deploying, and operating production ML systems at scale.
• 5+ years in deep learning, NLP, and GenAI/LLM orchestration using frameworks such as PyTorch, TensorFlow, Scikit-learn, LangChain, and LlamaIndex.
• Proficiency in Java, Go, Scala, or C++ for high-performance backend systems, plus strong proficiency in Python and ML libraries including NumPy, Pandas, PyTorch, TensorFlow, Scikit-learn, LangChain, LangSmith, and DSPy.
• Experience with distributed processing and high-throughput storage, including Spark, Flink, Kafka, ClickHouse, Pinecone, or Milvus.
• Knowledge of RAG architectures, LLM fine-tuning, intent classification, recommendation engines, MCP tooling, structured agentic execution, and multi-agent orchestration.
• Experience with EDA on multi-tenant execution logs, prompt/response accuracy analysis, vector embeddings, feature stores, and multi-tenant data isolation.
• Experience with model building, foundation model adaptation, prompt engineering, fine-tuning, low-latency inference, and the ML lifecycle using Kubeflow, MLflow, Airflow, or SageMaker.
• Experience deploying cloud-native ML systems with Docker, Kubernetes, gRPC/REST APIs, and CI/CD under 99.9% uptime and low-latency SLAs.
• Bachelor’s degree in Computer Science, Data Science, Machine Learning, Applied Mathematics, Statistics, or Engineering; a Master’s degree or PhD is strongly preferred.

Nice to have

• Master’s degree or PhD in a relevant field.

Culture & Benefits

• Flex work combines in-person collaboration with remote work, with at least 50% of each quarter spent in the office or field depending on the role.
• Eligible compensation may include the hirify.global Bonus Plan or role-specific commission or bonus and annual refresh stock grants.
• hirify.global provides comprehensive benefits and reasonable accommodations during the hiring process.
• Employment is subject to applicable US employment and fair-chance laws, with equal-opportunity protections.

Hiring process

• Applications must be submitted through hirify.global Careers; hirify.global does not charge recruiting, consulting, or coaching fees.
• Candidates may ask a hirify.global connection about the Employee Referral process if referred.