Position: Machine Learning Engineer
Location: Washington, dc MUST be onsite
Duration: 1 year+
Responsibilities:
- Work as part of a team of software engineers in conjunction with product stakeholders to understand business objectives, define technical requirements, and build features for production
- Apply NLP and ML knowledge to analyze and process voice queries using techniques like pattern matching, entity extraction, intent classification, and transformer models
- Support the application and fine-tuning of Generative AI models like Phi, Qwen, Llama, and Gemma to further our platform capabilities
- Contribute to building a scalable architecture that handles millions of requests per day
- Ensure the stability of our platform to serve our customers and assist with the deployment, monitoring, and troubleshooting of production systems
- Collaborate with teammates and contribute to design discussions, project planning, and code reviews
- Demonstrate a keen sense of responsibility and accountability towards the team’s work, its quality and timely delivery
Qualifications
- Bachelor’s or master’s degree in Computer Science, Machine Learning, or a related field
- 2 years of relevant work or internship experience
- Proficiency in programming languages like Python, Kotlin, and Java
- Experience with machine learning frameworks such as TensorFlow, PyTorch, and Keras
- Experience with natural language processing, machine learning, deep learning, optimization techniques, and evaluation methodologies
- Experience with or exposure to LLMs and integrating them with complex real-time data processing and low-latency systems including methods for optimizing LLM prompts and using a RAG architecture
- Experience with or exposure to cloud platforms (AWS) for deploying and managing ML models and its supporting architecture
- Experience with handling multi-lingual data and building systems that support multiple languages
- Experience researching new ideas, formulating creative solutions and presenting sophisticated ideas to technical and non-technical audiences
