The Role
Did you know? Alternative investing has the potential to generate higher returns compared to traditional investments over the long term. AI and Machine Learning are revolutionizing the way alternative investments are managed and analyzed. Investors are using these technologies to gain insights, see opportunities, and optimize their investment strategies.
Addepar is building solutions to support our clients' alternatives investment strategies. We’re using AI to automate and streamline ingestion and analysis of alternatives investment data. We are currently seeking a Machine Learning Engineer to join our Alternatives Data Management team. In this role, you will have the opportunity to apply the newest technology stacks to build and improve proprietary trained models that transform unstructured information into accurate financial data. If you've designed complex scalable systems, or worked with great teams on hard problems in financial data, or are just interested in solving really hard technical problems, come join us!
Addepar takes a market-based approach to pay. A successful candidate’s starting pay will be determined based on the role, job-related skills, experience, qualifications, work location, and market conditions. The range displayed on each job posting reflects the minimum and maximum target base salary for roles in Colorado, California, and New York.
The current range for this role is $125,000 - $195,000 + bonus + equity + benefits.
Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Additionally, these ranges reflect the base salary only, and do not include bonus, equity, or benefits.
What You’ll Do
- Design, build and train supervised and unsupervised machine learning models.
- Design and evolve machine learning pipeline for applications across the stack.
- Optimize machine learning and relevant data processing code for scale and robustness
- Document software functionality, system design, and project plans; this includes clean, readable code with comments.
Who You Are
- Proficiency with machine learning methodologies.
- Good knowledge of hosted and open source ML services like AWS SageMaker, Google Cloud ML, TensorFlow, Pytorch or others
- Experience with methods and tools (Textract, ABBYY) for extracting relationships, structure and text from documents and/or general natural language processing skills
- Proficiency in Python, R or other programming languages
- Experience working with Relational or NoSQL database storage
- Ability to communicate with all levels of collaborators on a technical level.
- A strong ownership mentality and aim to take on the most ambitious problems.
- AWS experience is a plus.
- B.S., M.S., or Ph.D. in Computer Science or similar technical field of study (or equivalent practical experience.).
