AI and Machine Learning Engineer, Senior
2 days ago
As a seasoned engineer, you will play a critical role in delivering customer-focused solutions by leveraging machine learning (ML) techniques to conduct statistical analyses on business processes. Your technical expertise and problem-solving skills will be essential in supporting solutions to global challenges across various sectors, including fraud detection, cancer research, and national intelligence.
In this role, you will collaborate with a community of research and experimentation leaders, software and IT operations engineers, AI and ML experts, data scientists, solution architects, systems engineers, and product owners to deliver world-class solutions. Your advanced solutioning skills and extensive technical expertise will drive innovation that is applicable across multiple client domains as they navigate the landscape of AI or ML solutions, tools, and frameworks.
Key Responsibilities:
- Apply best-fit ML algorithms and generative AI technologies to own and define the direction of mission-critical solutions.
- Collaborate with cross-functional teams to deliver world-class solutions.
- Develop and maintain models that learn from data and build purpose-driven generative AI solutions.
Requirements:
- 3+ years of experience with AI, ML, or software engineering to build customer-facing solutions and products.
- 2+ years of experience with LLM repos, including HuggingFace and API integration and development with RESTful APIs.
- 2+ years of experience with LLM frameworks and tools, including LangChain, LlamaIndex, FastAPI, Flask, or Streamlit and programming languages, including Python, Scala, or Java.
- 2+ years of experience with integrating LLMs, including Llama, Mixtral, or GPT-4, generative pre-trained transformer (GPT) models, or multi-modal models with applications or user interfaces.
- 2+ years of experience in working with ML libraries such as Scikit-learn, Pandas, TensorFlow, or Keras.
- 1+ years of experience with leveraging vector databases for Retrieval Augmented Generation.
- 1+ years of experience with cloud platforms, including Azure AI Studio or ML, AWS Bedrock or SageMaker, or GCP Vertex AI and MLOps, including CI/CD, model training or testing, deployment, or monitoring.
- 1+ years of experience with HTML, CSS, JavaScript, and common front-end frameworks.
- Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements.
- Bachelor's degree.
Nice to Have:
- Experience with working in collaborative, interdisciplinary team environments, consisting of data scientists, ML engineers, and domain experts.
- Experience in working with federal clients.
- Experience with container technologies, including Docker or Kubernetes.
- Experience with finetuning LLMs.
- Knowledge of evaluating generative AI models and model output and applying responsible AI principles to LLMs.
- Knowledge of LLMOps.
- Ability to distill complex technical concepts into easily understandable summaries consumable by business leaders with a non-technical background.
- Possession of excellent verbal and written communication skills.
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