As an Applications Dev Analyst here at Honeywell, you will lead application development, collaborate with teams, ensure coding standards, and mentor juniors. Your role will drive innovative software solutions and shape our tech landscape.
ResponsibilitiesKEY Responsibilities
• Apply strong expertise across Data Science, Machine Learning, and Generative AI to design, develop, and productionize advanced analytical, predictive, and GenAI‑driven solutions, grounded in statistical modeling and data thoughtfulness
• Build end‑to‑end ML and GenAI pipelines on Databricks, and own the MLOps lifecycle using MLflow, ensuring alignment with business objectives and successful delivery of actionable insights
• Design and implement and productionize Agentic AI solutions, including multi‑agent workflows, tool‑calling agents, and autonomous decision pipelines, to address complex business use cases
• Ensure ML and GenAI model performance, uptime, scalability, observability, and monitoring, maintaining high standards of code quality and thoughtful system and model design
• Build and maintain production‑grade CI/CD pipelines for ML and GenAI workloads using GitHub Actions and Databricks Workflows
• Apply strong thoughtfulness and problem‑solving skills to address complex data and AI demands, including LLM fine‑tuning, prompt engineering, RAG optimization, and agent orchestration, to generate valuable business insights
• Collaborate with cross‑functional teams and mentor junior data scientists, clearly communicating Data Science, ML, and GenAI concepts to both technical and non‑technical stakeholders
MUST HAVE
• Bachelor’s degree or Advanced degree in Computer Science, Statistics, Mathematics, or related discipline
• 5–8 years of strong experience in Data Science and Machine Learning, including Time‑series forecasting, Regression, Classification, Clustering, Deep Learning, NLP, and Optimization algorithms, using Python in a programming‑intensive role
• 5–8 years of strong experience in Python and PySpark coding, preferably in large‑scale, distributed data environments
• 5–8 years of hands‑on experience with Azure or AWS Databricks, including Spark optimization, Databricks Workflows, and production deployments
• 4+ years of experience in end‑to‑end ML model development and MLOps architecture, including model deployment, monitoring, and lifecycle management
• Strong expertise in MLflow for experiment tracking, model registry, versioning, governance, and production model deployments
• 5-8 years of industry experience with popular ML frameworks such as Keras, TensorFlow, PyTorch, HuggingFace Transformers, and libraries like scikit‑learn
• Strong hands‑on experience across Generative AI and advanced ML domains, including Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG) systems, prompt engineering, embedding strategies, and applied NLP
• Hands‑on experience designing and building Agentic AI solutions using modern agent orchestration and tool‑calling frameworks such as LangChain, LangGraph, CrewAI, or equivalent frameworks
• Strong experience with GitHub Actions, CI/CD pipelines, and MLOps frameworks
• Excellent knowledge and experience or exposure to the Dataiku platform
• Excellent communication skills with a strong people‑oriented, collaborative, and mentoring mindset
Skills Required
- Bachelor's or advanced degree in Computer Science, Statistics, Mathematics, or related discipline
- 5-8 years experience in Data Science and Machine Learning (time-series, regression, classification, clustering, deep learning, NLP, optimization) using Python
- 5-8 years hands-on Python and PySpark coding experience in large-scale, distributed data environments
- 5-8 years hands-on experience with Azure or AWS Databricks including Spark optimization, Databricks Workflows, and production deployments
- 4+ years experience in end-to-end ML model development and MLOps architecture, including deployment, monitoring, and lifecycle management
- Strong expertise in MLflow for experiment tracking, model registry, versioning, governance, and production deployments
- 5-8 years industry experience with Keras, TensorFlow, PyTorch, HuggingFace Transformers, and scikit-learn
- Hands-on experience with Generative AI: LLM fine-tuning, prompt engineering, RAG optimization, embedding strategies, applied NLP
- Hands-on experience designing and building Agentic AI solutions using LangChain, LangGraph, CrewAI or equivalent frameworks
- Strong experience building production-grade CI/CD pipelines for ML and GenAI workloads using GitHub Actions and MLOps frameworks
- Excellent knowledge and experience or exposure to the Dataiku platform
- Excellent communication, collaboration, and mentoring skills to convey technical concepts to technical and non-technical stakeholders
The Aerospace Corporation Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about The Aerospace Corporation and has not been reviewed or approved by The Aerospace Corporation.
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Retirement Support — The 401(k) plan provides a company‑paid contribution of 8–12% based on years of service with immediate eligibility and vesting, and eligible employees can access retiree medical benefits.
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Leave & Time Off Breadth — Paid time off includes 15 vacation days (rising to 20 after five years), nine paid holidays, and unlimited sick time for exempt employees with accruals for non‑exempt staff.
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Flexible Benefits — Flexible work models include a 9/80 schedule with alternating Fridays off, supported by backup care services, an EAP, relocation assistance, and home‑office stipends where applicable.
The Aerospace Corporation Insights
What We Do
The space enterprise has been transformed by rapid change and growth. New vehicles for national security space, a more rapid launch cadence, proliferated satellite constellations, the pursuit of interplanetary exploration, and thriving commercial ventures are changing the nature of the space industry. The Aerospace Corporation (Aerospace) is a leading architect for U.S. space programs, shaping efforts to outpace threats to our national security while cultivating the technologies needed to further this new era of space commercialization and exploration. Aerospace works across the space enterprise in service of the public interest. In addition to supporting the Department of Defense and the Intelligence Community, our customers include NASA, NOAA, numerous federal agencies, and commercial space — all of whom benefit from our deep technical knowledge. We only pursue business related to the space mission and complementary fields, operating as the nation’s trusted partner to solve the toughest challenges and develop reliable and innovative technologies. Innovation in space occurs when people have the freedom to imagine and do. At Aerospace, we take pride in our readiness to solve some of the most complex challenges in the space enterprise.
Why Work With Us
We are a non-profit corporation chartered by the government to work on the hardest problems in space. We employ technical experts in every discipline of space-related science and engineering who touch every part of the US space program. Come join us as we make an impact bigger than ourselves.
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