À propos
This is a direct‑hire, full‑time position with salary and benefits.InDev provides a comprehensive benefits package, Medical, Dental, Vision, 401k with match, Flexible Spending Account, and Paid Time Off (PTO)—including vacation and holiday pay.
YOUR FUTURE DUTIES AND RESPONSIBILITIES Model Development
Collaborate with data scientists and subject matter experts to develop machine learning models using curated datasets.
Conduct experiments, prototypes, and proof‑of‑concepts to validate and refine model performance.
Build scalable, reusable training pipelines using Databricks notebooks and MLflow.
Implementation & Optimization
Implement and optimize Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG) systems, and AI agent architectures for enterprise use cases.
Deployment & MLOps
Operationalize models using robust CI/CD workflows.
Deploy ML solutions via MLflow, AWS SageMaker, or custom APIs.
Monitor production performance for accuracy, drift, and latency; manage retraining cycles and model governance.
Data Integration & Architecture Alignment
Partner with Data Engineering to align ML pipelines with the Bronze, Silver, and Gold layers of a Medallion Architecture.
Engineer high‑quality features and maintain training and inference pipelines.
Cloud & Platform Engineering
Utilize AWS services such as S3, EC2, Lambda, SageMaker, and Step Functions for scalable ML workloads.
Collaboration & Documentation
Document ML artifacts, processes, and performance outcomes clearly and comprehensively.
Collaborate within agile teams, support project ceremonies, and maintain stakeholder communication.
Mentor junior team members and share best practices.
QUALIFICATIONS
5+ years of experience in ML Engineering or Applied Machine Learning.
Strong Python programming skills.
Hands‑on experience with major ML frameworks (e.g., scikit‑learn, XGBoost, PyTorch, TensorFlow).
Proficiency with Databricks, MLflow, and PySpark.
Solid understanding of the end‑to‑end model lifecycle and MLOps best practices.
Experience with AWS‑based data infrastructure and DevOps workflows.
Proven ability to productionize ML models and integrate them into business systems.
Strong understanding of mathematics and statistics relevant to ML and AI.
Experience with supervised, unsupervised, and deep learning techniques.
Solid background in software engineering principles and best practices.
Hands‑on experience with training frameworks such as TensorFlow, PyTorch, or Hugging Face.
Practical experience building and deploying LLMs, RAGs, and AI agent systems.
Demonstrated expertise with Databricks for data engineering and ML pipeline development.
Excellent communication and teamwork skills.
NICE TO HAVES
Experience building rapid‑prototype AI model interfaces with Streamlit, Gradio, or similar tools.
Business acumen with the ability to align ML solutions with organizational goals.
Experience optimizing compute and storage resources for performance and cost efficiency.
Clearance:
Must be a U.S. Citizen and be able to obtain a U.S. Federal government client badge, and will be required to pass a government background investigation. Candidates with active DOT clearance preferred.
WHY INDEV
Innovative Environment: Join a team that thrives on creativity and innovation, where your ideas are not only heard but encouraged.
Meaningful Impact: Contribute to projects that directly impact federal agencies, driving positive change on a national scale.
Dynamic Collaboration: Work alongside diverse experts who are passionate about pushing boundaries and making a difference.
Agile Mindset: Embrace Agile methodologies that encourage flexibility, adaptability, and rapid growth.
Learning Culture: Enjoy ongoing learning opportunities and professional development to expand your skill set.
Cutting‑edge Tech: Engage with the latest technologies and tools in the data integration landscape.
If you're ready to embark on a journey of innovation, collaboration, and impact, InDev welcomes you to join our team. Let's shape the future together.
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Compétences linguistiques
- English
Avis aux utilisateurs
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