Machine Learning Engineer

1 week ago


Denver, United States Actalent Full time

Looking for a Machine Learning/ AI Engineer position.... I have just the job for you Are you an AI/ML enthusiast seeking exciting challenges? We’re looking for an AI/ML Engineer to join our team. In this role, you’ll tackle a diverse range of problems, from object detection and natural language processing to reinforcement learning and large language models. Our team includes exceptional researchers and software developers who are eager to mentor and share their expertise. Responsibilities: Algorithm Implementation: Collaborate with a small team of developers and researchers to implement machine learning algorithms. These algorithms will address a wide array of challenges faced by our diverse customer base. Data Analysis: Dive into large multi-domain datasets, including images, text, and graph data. Identify statistically relevant features to construct models that empower analysts with actionable insights. Model Training and Deployment: Leverage cloud services to train and deploy ML models. Your work will contribute to cutting-edge applications. Staying Current: Keep up-to-date with the latest developments in AI/ML. Review relevant publications and apply cutting-edge concepts to both defense and commercial applications. Technical Documentation: Write clear technical documentation to support code, program capabilities, and user guides. Skills: Object Detection Natural Language Processing Imagery Analysis Algorithm Development Experience with PyTorch and TensorFlow Proficiency in Python Top Secret Clearance REQUIRED Additional Qualifications: Leadership Experience: You’ve led interdisciplinary teams of researchers and software developers. AI/ML Domains:Large Language Models: Familiarity with incorporating them into new areas and applications. Object Detection Algorithms: Knowledge of YOLO and Faster-RCNN. Natural Language Processing Algorithms: Experience with Transformers and RNNs. Cross-Domain Application: Applying Transformer-based architectures beyond NLP (e.g., computer vision). Generative Adversarial Networks and Variational Autoencoders Reinforcement Learning: Familiarity with OpenAI Gym, RLlib, and Stable Baselines. Clustering Algorithms and Deep Neural Networks Tracking & Fusion and Pattern-of-Life Algorithms Machine Learning Libraries and Frameworks: Proficiency with tools like Hugging Face and LangChain. Linux Experience AWS Cloud Computing Resources: Familiarity with EC2, S3, Lambda, etc. Join us at the forefront of AI innovation and help shape the future of machine learning



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