Staff Machine Learning Engineer

Summary

Join Flowcode's growing ML team as a passionate Staff Machine Learning Engineer. You will design and deploy models, contribute to core product and analytics systems, and influence strategic decisions. This role involves working with structured and unstructured data, building scalable ML infrastructure, and establishing best practices. Ideal candidates thrive in fast-paced environments and collaborate effectively with engineering, product, and analytics teams. The position offers the opportunity to drive impact at scale and build novel ML applications and pipelines. The role is remote or hybrid in the NYC office, with a competitive salary and equity.

Requirements

• 5+ years of software or ML engineering experience, including 3+ years working on production ML systems
• Strong skills in Python and SQL, with fluency in ML tools such as PyTorch, scikit-learn, transformers, and pandas
• Hands-on experience with LLMs and transformer architectures (e.g., GPT, BERT), including embedding generation and prompt engineering
• Solid experience deploying ML models into production using Docker, Kubernetes, or cloud-based pipelines (e.g., AWS, GCP)
• Experience building end-to-end solutions using LLMs for various applications such as RAG, classification, and summarization pipelines
• Strong data wrangling and engineering foundations; comfortable working with unstructured and complex data
• Excellent communication skills and a track record of working cross-functionally with product and engineering teams
• Experience with traceability and observability tools in deployed systems (e.g., Langfuse, Datadog)

Responsibilities

• Design and deploy ML models using traditional supervised, unsupervised, and semi-supervised techniques on unstructured, multidimensional datasets
• Design and deploy solutions that utilize open-source and proprietary LLMs (Anthropic, OpenAI, Ollama, etc.)
• Create insightful visualizations using tools like matplotlib, seaborn, plotly, etc
• Build and scale ML infrastructure for analytics, consumer products, business intelligence, and model pipelines
• Develop with Python, SQL, and libraries such as PyTorch, Langchain, huggingface-transformers, scikit-learn, and pandas
• Demonstrate technical ownership of end-to-end ML-based solutions
• Collaborate with engineering, product, and analytics teams to ensure successful deployment and adoption of ML-driven solutions
• Drive project scoping and build novel ML applications and pipelines

Preferred Qualifications

• Familiarity with system architecture and common service paradigms (e.g., CRUD, cron-jobs)
• Familiarity with experiment design, including A/B testing and causal inference methods
• Experience with MLOps tools (e.g., MLflow, Kubeflow, SageMaker)
• Comfort with visualization and presentation of high-dimensional data using modern tools
• Background in statistics, optimization, or computer vision is a plus
• Experience with clustering and anomaly detection using various supervised and unsupervised techniques
• Experience with datastores such as Snowflake, PostgreSQL, Singlestore, Redis, Milvus, etc
• Experience with streaming technologies such as Kafka, Flink, NATs, etc

Benefits

• Remote or Hybrid in NYC Office
• The current range for this role is up to $215-250K OTE plus equity