MLOps Engineer

Fractal Labs
New York
Workplace: OnsiteFull timeUSD 120,000 - 140,000 annuallyFunction: Software EngineeringSkills: ["Communication","Collaboration","Documentation","Incident diagnosis"]

Build and productionize a portfolio of machine learning solutions in purchase and underwriting by designing and operating the inference layer, data and feature pipelines, and batch/real-time parity. You’ll implement FastAPI model-serving services (sync/async), containerize and deploy them, and use Databricks/PySpark to create reproducible pipelines. Focus on reliability and observability, incident diagnosis, and strong engineering practices with CI/CD, testing, and clear documentation for internal ownership.

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FursaFursa
Fractal Labs
Fractal Labs
1 month ago

MLOps Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Status: Live

Job Summary

Build and productionize a portfolio of machine learning solutions in purchase and underwriting by designing and operating the inference layer, data and feature pipelines, and batch/real-time parity. You’ll implement FastAPI model-serving services (sync/async), containerize and deploy them, and use Databricks/PySpark to create reproducible pipelines. Focus on reliability and observability, incident diagnosis, and strong engineering practices with CI/CD, testing, and clear documentation for internal ownership.
Location: New York
Workplace: Onsite
Employment Type: Full time
Job Function: Software Engineering
Seniority: Mid level

Key Responsibilities

  • •Design and build FastAPI model-serving services with robust request/response contracts, authentication/authorization, validation, logging, tracing, and metrics.
  • •Implement queue-based asynchronous serving with producers/consumers, retries, idempotency, back-pressure, dead-letter handling, and end-to-end request traceability.
  • •Own data preprocessing, transformation, and feature engineering code; refactor notebook/script logic into modular, tested, reusable components.
  • •Build reproducible training and batch inference pipelines on Databricks and PySpark, including model artifact/version management and promotion across environments.
  • •Ensure parity and reliability across the ML lifecycle by aligning feature definitions across training/batch/real-time and implementing monitoring, drift/data-quality checks, and production incident fixes.

Pay and Benefits

Salary: USD 120,000 - 140,000 annually
Perks:Health InsuranceDentalVisionLife InsuranceDisability401kPaid HolidaysParental Leave

Key Requirements

  • •Deep hands-on Python for data engineering and application development, with comfort across SQL, PySpark, and shell scripting.
  • •Production experience building services with FastAPI (or comparable Python web framework), including auth, validation, error handling, and observability.
  • •Experience with queue-based asynchronous processing systems (Kafka, RabbitMQ, SQS, Redis Streams, Celery, or equivalent) and operational concerns like retries, idempotency, back-pressure, and dead-letter queues.
  • •Strong Docker and containerization skills; comfortable with Kubernetes concepts.
  • •Hands-on Databricks experience with MLFlow and distributed compute in Spark, plus familiarity with common ML libraries (scikit-learn, XGBoost, PyTorch or similar).
Skills:CommunicationCollaborationDocumentationIncident diagnosis
Tech Stack:PythonSQLPySparkFastAPIDockerKubernetesDatabricksMLFlowSparkScikit-learnXGBoostPyTorchKafkaRabbitMQSQSRedis StreamsCeleryJenkinsGitHub ActionsAirflow

Company Brief

Fractal Labs
Provides AI-driven analytics, decision intelligence, and engineering solutions to Fortune 500 companies, helping enterprises apply advanced analytics and machine learning for marketing, supply chain, finance, and customer experience transformation.
Industry: Consulting
Company Size: Enterprise (1,001+ employees)
Growth: Established Company
Headquarters: New York, United States
Founded: 2000
WebsiteLinkedIn