Machine Learning Engineer
Designs, develops, and deploys ML models focused on fine-tuning multimodal LLMs for fraud detection and application automation in financial profiles. Requires 3+ years experience with Python, PyTorch, and expertise in information extraction from financial documents.
About the job
Key Responsibilities
- Work autonomously to design, develop and deploy machine learning models
- Analyze large datasets to uncover insights and trends that inform product development and personalized customer experiences
- Continuously monitor and improve the performance of deployed models, ensuring they meet business objectives and scalability requirements
- Stay up to date with the latest advancements in machine learning, AI, data science and engineering, and apply this knowledge to improve our products and services
Desirable Traits
- 3+ years of experience in a Machine Learning or Data Engineering role, with a strong proficiency in Python and ML frameworks like PyTorch required
- Proven ability to improve models for key information extraction, including named entity recognition and matching, and financial document classification
- Experience with active learning, HITL driven workflows; working with large labeling and quality teams is a plus
- Strong problem solving skills, with the ability to think critically and creatively
- Excellent communication and interpersonal skills, capable of explaining complex operational information in an understandable way
- A proactive, curious mindset with a relentless pursuit of excellence and innovation in tackling complex problems
Compensation
- Competitive salary, comprehensive equity package, and substantial benefits
- Base salary range: $175k - $250k+ per year (in addition to a large equity package and full benefits)
Skills
Python, PyTorch, Machine Learning, LLMs, Named Entity Recognition, Active Learning, Human-In-The-Loop, Data Analysis
Similar jobs
ML Engineering jobs
LangChain
New York, NYBuild and teach reliable AI agent systems through customer workshops, technical content, guidance, and reference implementations. The role requires strong Python and agent-development experience plus a background delivering customer-facing technical training.
Roboflow
San Francisco, CA
Build reinforcement-learning environments, evaluations, datasets, and scalable infrastructure for frontier AI capabilities. The role suits a high-agency generalist engineer with experience in agents, evaluations, or RL workflows and strong communication skills.
Beacon Biosignals
Boston, MADevelop and productionize machine- and deep-learning algorithms for biosignal and EEG data used in medical devices, clinical development, and diagnostics. The role requires 4+ years of industry experience, DSP and statistics expertise, PyTorch proficiency, and familiarity with regulated environments and production ML practices.
Applied Intuition
Sunnyvale, CA
Develop and deploy ML-first behavior prediction and planning systems for autonomous vehicles, forecasting the motion and interactions of road users. Requires a bachelor's degree, deep learning lifecycle expertise, and at least three years of production software experience with C++ or Python.
Instacart
Canada
Develop and deploy machine learning systems for Instacart’s advertising ecosystem, spanning data pipelines, model architectures, serving, experimentation, and optimization. The role requires a graduate degree and strong programming, analytical, and collaboration skills, with experience in large-scale ML systems preferred.