Audio Forensics Jobs (NOW HIRING)

Job Summary:
Charles River Associates is a leading global consulting firm that provides independent economic and financial analysis. They are seeking an Associate Principal/Forensic AI Engineer to lead projects at the intersection of artificial intelligence and forensic investigation, supporting clients in responding to allegations of misconduct and developing AI-based solutions.
Responsibilities:
• Support our dev team in building unique AI-based solutions for our clients.
• Lead and support technical vision and execution for forensic investigations involving AI-generated content, large language model misuse, deepfake media, synthetic voice and video, and AI-enabled fraud or misconduct.
• Develop, deploy, and validate deepfake detection pipelines and multimodal AI forensic tooling to analyze and authenticate text, image, audio, and video evidence at scale.
• Perform AI content attribution and provenance analysis, including authorship attribution for LLM-generated text, model fingerprinting, training data inference, and C2PA (Coalition for Content Provenance and Authenticity) manifest analysis.
• Apply LLM-based analytical frameworks, including retrieval-augmented generation (RAG) pipelines, structured output generation, and document intelligence, to accelerate investigation workflows and enhance analytical throughput.
• Conduct adversarial prompt analysis, prompt injection detection, and evaluation of AI system vulnerabilities in the context of client incidents, regulatory matters, and litigation.
• Design and build forensic data pipelines and investigatory tooling used to process and analyze large and varied datasets, including unstructured text corpora, media archives, model outputs, and system logs.
• Serve as technical subject matter expert advising legal counsel and corporate executives on complex AI, generative media, and data integrity challenges, translating sophisticated technical findings into defensible, plain-language expert reports and testimony suitable for judicial and regulatory audiences.
• Deliver training programs for clients and internal colleagues on responsible LLM use, AI-generated content identification methodologies, forensic readiness, and AI governance frameworks.
• Lead cross-functional engagements requiring coordination across technical analysis, legal strategy, digital forensics, and stakeholder communication under aggressive deadlines.
• Mentor junior team members.
• Contribute to internal initiatives, thought leadership, and practice development.
Qualifications:
Required:
• Bachelor’s degree required; Computer Science, Electrical Engineering, Data Science, Computational Linguistics, Information Systems, or a related technical field.
• 8–10+ years of progressive experience in machine learning engineering, AI research, digital forensics, data science, or a closely related technical field, with deep expertise in at least two of the following domains: Development, fine-tuning, evaluation, or production deployment of large language models (LLMs) or generative AI systems; Synthetic media detection, deepfake analysis, or AI-generated content forensics; Natural language processing, computational linguistics, or authorship attribution; Digital forensics, incident response, eDiscovery, or cybercrime investigation; Consulting delivery, expert witness services, or client-facing technical advisory roles in a litigation or regulatory context.
• A representative portfolio of project contributions, including open-source contributions, published research, technical blog posts, or other observable works, demonstrating sustained, applied AI proficiency across investigation-relevant domains.
• Demonstrated ability to conduct or support expert witness engagements, produce legally defensible forensic reports, and communicate complex technical findings to non-technical audiences including judges, regulators, and corporate executives.
• Familiarity with AI governance and risk management frameworks, including the NIST AI Risk Management Framework, ISO/IEC 42001:2023 (AI Management Systems), and the OWASP Generative AI Security guidelines.
• Advanced proficiency in Python; competency with PyTorch and/or TensorFlow for deep learning model development and evaluation; data analysis using pandas, NumPy, and scikit-learn; and SQL for structured data querying and investigation support.
Preferred:
• Graduate degree (M.S. or Ph.D.) in Machine Learning, Artificial Intelligence, Computer Vision, Natural Language Processing, or a closely related discipline preferred.
• LLM Proficiency: Deep understanding of large language model architectures (transformer-based models including GPT, LLaMA, Mistral, Gemma, and related families); proficiency with fine-tuning methodologies including LoRA, QLoRA, and instruction tuning; and experience with alignment techniques (RLHF, RLAIF, DPO).
• LLM Ecosystems and Tooling: Proficiency with the HuggingFace ecosystem (Transformers, PEFT, Datasets, Evaluate, TRL); major LLM inference frameworks (vLLM, llama.cpp, Ollama); and orchestration frameworks including LangChain and LlamaIndex.
• Retrieval-Augmented Generation (RAG) Pipelines: Experience building, evaluating, and optimizing RAG pipelines using vector databases (Pinecone, Weaviate, ChromaDB, pgvector) and embedding models, including chunking strategy, retrieval evaluation, and hybrid search.
• Deepfake Detection and Synthetic Media Forensics: Competency in deepfake detection methodologies including CNN- and transformer-based detection models (trained on FaceForensics++, DFDC, or equivalent datasets); GAN architecture analysis; multimodal artifact inspection (lip synchronization, temporal consistency, audio-visual misalignment); and pixel-level manipulation detection tools (e.g., Amped Authenticate, Sensity AI).
• Content Provenance and Authentication: Understanding of content provenance standards including C2PA (Coalition for Content Provenance and Authenticity), cryptographic content credentials, digital watermarking approaches (including SynthID), and blockchain-based authenticity verification.
• Text Forensics and Authorship Attribution: Experience with NLP-based forensic methodologies including stylometric analysis, semantic embedding-based authorship attribution, human vs. machine-generated text classification, and LLM source attribution (model fingerprinting, training data membership inference).
• Computer Vision and Multimodal Analysis: Experience with computer vision libraries (OpenCV, torchvision, PIL/Pillow) and audio/video processing tools for media forensics, including EXIF metadata analysis, sensor pattern noise analysis, and compression artifact forensics.
• Cloud and Infrastructure: Familiarity with cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure Machine Learning) and containerization approaches (Docker, Kubernetes) for deploying and managing AI forensic tooling in enterprise environments.
• Data Engineering: Experience with data engineering frameworks and tools including Apache Spark, Airflow, and modern data warehousing platforms (Snowflake, BigQuery, Redshift) for processing and analyzing large-scale unstructured and semi-structured datasets.
Company:
Charles River Associates is a consulting firm specializing in financial, litigation, regulatory, and management consulting. Founded in 1965, the company is headquartered in Boston, USA, with a team of 1001-5000 employees. The company is currently Late Stage.