Reports to: Head of AI
Location: Latin America
Compensation: $65K - $95K
ReflexAI brings the best in machine learning and natural language processing to mission-driven, people-centric organizations via innovative tools that transform how they train, develop, and empower their frontline teams. The AI / ML team at ReflexAI is involved in multiple large-scale projects, including ReflexAI’s highly visible development of a tool that trains veterans to support each other through mental health challenges.
About this role
As a Senior Machine Learning Engineer at ReflexAI, you will be involved in multiple large-scale projects across various phases of delivering ML products. To be successful, you should have significant experience with NLP, LLMs (e.g., GPT, BERT, T5), and ML system design. You will also collaborate with engineering, product, and business team members. You should be excited about being a part of a fast-paced startup that makes a real impact across important industries including crisis response, public safety, healthcare, and more.
What you’ll do
- Ideate, develop, and deploy scalable and cost-efficient machine learning and natural language processing models
- Build scalable infrastructure for training, evaluating, and serving models
- Analyze datasets to improve current approaches and prototype new ideas
- Develop tools and processes for sourcing, analyzing, labeling, and storing conversation data
- In all key responsibilities, view work through critical ethical lenses including fairness, quality, and trust
Requirements for a great fit
- Significant experience (typically 3+ years) of building production-grade machine learning models in industry and/or academic research settings
- Expertise in various facets of NLP, such as conversational dialogue, speech recognition, text-to-speech, natural language generation, text classification, question-answering, chatbots, and text summarization
- Strong programming skills in Python and deep-learning / NLP tools (Scikit-learn, Pandas, PyTorch, Tensorflow, NLTK, spaCy, Jupyter)
- Experience building end-to-end scalable ML infrastructure with on-premise or cloud platforms including Google Cloud Platform (GCP), Amazon Web Services (AWS) or Azure
- Strong teamwork skills including communication and collaboration with both technical and non-technical team members
- Open mindedness as demonstrated by ability to consider other perspectives and feedback, ability to engage in discussions with professionalism and empathy, and a strong desire to learn
- Compensation ranges are for Latin America-based team members. Stock options are offered in addition to cash compensation.