Dark Wolf Solutions is seeking a driven and innovative AI/ML Engineer to join our team in Tampa, FL. The successful candidate will play a key role in developing innovative AI/ML solutions that directly support a critical mission for a key DoD customer. The AI/ML Engineer instrumental in designing, implementing, and deploying advanced AI/ML models for a cutting-edge project, working alongside experienced professionals and shaping the future of this initiative. This position requires on-site support at MacDill Air Force Base in Tampa, FL. Key responsibilities include, but are not limited to:

• Enabling AI/ML Data pipelines as part of an AI/ML Data Factory.
• Testing and validating the performance of the AI/ML Data Factory.
• Assisting with data acquisition, ingestion, and tagging; data exploration and understanding; feature extraction and analysis; data engineering and conditioning; data labeling; and constructing, training, and validating AI/ML Datasets.
• Implementing and fine-tuning LLMs (e.g., OpenLLM, Falcon, Mistral, LLaMA, GPT-NeoX) using frameworks like Hugging Face Transformers, DeepSpeed, and LoRA/QLoRA for parameter-efficient tuning.
• Train and deploy LVMs (e.g., SAM, CLIP, DINOv2, YOLOv8) using PyTorch, Detectron2, or OpenCV for ISR and geospatial intelligence fusion, while emphasizing the critical importance of acquiring, sanitizing, and curating high-quality datasets to ensure effective model training and real-world applicability.
• Utilizing ONNX Runtime, TensorRT, and OpenVINO for quantization and hardware-accelerated inference on edge devices (e.g., NVIDIA Jetson, Intel Movidius, ARM-based SOCs).
• Leveraging Ray, Kubeflow, or MLflow to orchestrate distributed training and model lifecycle management across hybrid environments (cloud/tactical edge). 
• Integrating AI analytics with TAK, ATAK plugins, WebTAK Plugins, and WinTAK to enrich Common Operating Pictures.
• Building edge-compatible pipelines using NVIDIA Triton Inference Server, TorchServe, or TF Lite to enable AI-as-a-service in contested and disconnected networks.
• Deploying containerized AI workloads using Docker, K3s, and Istio across Zero Trust micro-segmented environments following NSA Kubernetes STIG guidance.
• Implementing multimodal fusion and prompt engineering with LangChain, Haystack, or Lamini to build interactive agents capable of natural-language responses based on live mission data.
• Applying Federated Learning and SWA (Stochastic Weight Averaging) to allow for decentralized model training across secure enclaves or forward-operating nodes.
• Hardening model integrity and reliability with Adversarial Robustness Toolbox (ART), MLFlow Audit Trails, and compliance with DoD AI Ethical Principles.
• Designing data acquisition and preprocessing workflows with Apache Kafka, Airbyte, and Apache NiFi for ingesting telemetry, EO/IR, and SIGINT sources into LLM/LVM training pipelines. 
• Using Elastic Stack, OpenSearch, and Neo4j to store, search, and graph-represent AI-extracted insights within a mission-relevant knowledge base.

Required Qualifications: 

• 5+ years of experience performing data engineering efforts to include: data architecture, modeling, cleansing, ingesting, updating, and visualization
• 2+ years of experience working with Cloud environments
• 1+ year experience using scripting languages such as R, Python, or Javascript
• 1+ years experience using Big Data technologies and tools (e.g. Spark, Hadoop, Hive, Cassandra, Druid, Flink, Drill, Trino, NoSQL)
• Experience with a variety of open source and commercial ETL tools for preparing and loading data for AI/ML analytics
• Ability to manipulate raw data into effective visualization dashboards Ability to communicate end to end data outcomes visually
• Demonstrates a deep understanding of multiple database concepts
• Understanding of SQL
• Comfortable in a project startup environment 
• Bachelor’s degree in Computer Science, Information Technology, or a related field
• US Citizenship and an active Top Secret security clearance required

Desired Qualifications:

• Master’s degree in Information Systems, Computer Science, Engineering, or related field, or the equivalent combination of education, training and experience
• A cloud certification in AWS, Azure, or GCP