Senior AI/ML Engineer, Applied Machine Learning – Security Clearance
Red Cell Partners
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteSalary
💰 $175,000 - $225,000 per year
Job Level
Senior
Tech Stack
PythonPyTorchTensorflow
About the role
- Architect, Build, and Optimize ML Systems: Develop and deploy robust ML models that deliver high-impact results for real-world applications.
- Training Pipeline Development: Design and implement efficient, scalable pipelines to train and retrain ML models, ensuring they meet business needs.
- Fine-Tuning Large Language Models (LLMs): Continuously fine-tune LLMs to align with specific enterprise requirements, enhancing accuracy, relevance, and performance.
- Feedback Systems Design: Implement and refine feedback loops to iteratively improve the effectiveness of ML models over time.
- Cross-Functional Collaboration: Work closely with product and business teams to understand and translate requirements into ML solutions that provide tangible outcomes.
- Stay Current with ML Advancements: Keep up with the latest in ML research and best practices, applying insights to our ML infrastructure to ensure it remains at the cutting edge.
- Mentorship and Knowledge Sharing: Guide and mentor junior team members, fostering a culture of continuous improvement and technical growth.
- Technical Communication: Clearly and effectively communicate ML methodologies, results, and insights to non-technical stakeholders.
Requirements
- ML Systems Expertise: Proven experience in developing, optimizing, and deploying ML systems in production environments.
- Model Training and Pipeline Mastery: Strong background in building and managing end-to-end training pipelines for ML models.
- LLM Fine-Tuning: Extensive knowledge and hands-on experience in fine-tuning large language models for specific use cases and optimizing them for targeted outcomes.
- Framework Proficiency: Skilled in ML frameworks such as TensorFlow, PyTorch, or similar tools used in ML model development.
- Programming Skills: Proficient in Python with a focus on writing efficient, clean, and maintainable code for ML applications.
- Clear Communicator: Ability to distill complex ML concepts for both technical and non-technical audiences.
- Educational Background: Bachelor’s or Master’s degree in Machine Learning, Computer Science, Data Engineering, or a related field.
- Impactful ML Solutions: A track record of delivering and implementing machine learning solutions that have successfully driven value in real-world applications.
- Active Secret or Top Secret Clearance
Benefits
- 100% employer-paid, comprehensive health care including medical, dental, and vision for you and your family.
- Paid maternity and paternity for 14 weeks at employees' normal pay.
- Unlimited PTO, with management approval.
- Opportunities for professional development and continued learning with educational reimbursements.
- Optional 401K, FSA, and equity incentives available.
- Mental health benefits through TARA Mind.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
ML systemsmodel trainingtraining pipelinesfine-tuning large language modelsTensorFlowPyTorchPythonmachine learning solutionsscalable pipelinesfeedback systems
Soft skills
cross-functional collaborationmentorshiptechnical communicationclear communicatorcontinuous improvement
Certifications
Bachelor’s degree in Machine LearningMaster’s degree in Machine LearningBachelor’s degree in Computer ScienceMaster’s degree in Computer ScienceBachelor’s degree in Data EngineeringMaster’s degree in Data EngineeringActive Secret ClearanceTop Secret Clearance