Senior AI Engineer

9 days ago

Remote, WorldwideSenior

H1B Sponsor

Base Salary

$200k - $200k/yr

Responsibilities

Design and implement scalable AI/ML systems for space domain awareness and customer-facing insights.
Develop feature engineering pipelines, training datasets, model evaluation workflows, and production-grade machine learning models.
Deploy, monitor, optimize, and continuously improve models in real-time or near-real-time production environments.
Work with large-scale distributed sensor, orbital, telemetry, and geospatial datasets.
Partner with data engineering to improve data quality, scalability, and pipeline reliability.
Lead Agentic AI initiatives and establish best practices for model development, MLOps, reproducibility, and lifecycle management.
Mentor junior team members and influence technical and non-technical stakeholders.

Bachelor’s or master’s degree in computer science, artificial intelligence, machine learning, engineering, mathematics, physics, or equivalent experience.
5–7 years of experience in software engineering, machine learning engineering, or applied AI roles.
Eligibility to obtain and maintain a U.S. personnel security clearance and required ITAR authorizations.
Strong proficiency in Python and modern machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn.
Advanced SQL and large-scale data processing experience.
Proven experience developing and deploying production-grade machine learning models.
Experience with distributed data platforms such as Databricks and Spark.
Strong knowledge of statistical modeling, machine learning algorithms, experimental design, feature engineering, and training workflows.
Familiarity with MLOps practices, model versioning, monitoring, and lifecycle management.
Up-to-date familiarity with Agentic AI developments and strong communication and problem-solving skills.
Preferred experience building Agentic AI systems for time series, anomaly detection, or predictive modeling.
Preferred familiarity with Databricks ML, MLflow, Kafka, or Spark Structured Streaming.
Preferred background in sensor, telemetry, geospatial, orbital, aerospace, physics, or applied mathematics datasets.
Preferred experience with real-time or near-real-time model deployment, technical leadership, and mentoring junior data scientists.

Flexible remote or hybrid work opportunities.
Unlimited paid time off for most roles.
Comprehensive health, dental, and vision coverage.
Competitive salary, equity packages, bonus, and stock options.
Opportunity to work on complex space operations, defense, and security missions with real-world impact.
Access to commercial space operations and defense innovation.