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Senior Machine Learning Engineer
TegusUnited Statesfull_timeVerifiedPosted 22 May 2023
About the role
Tegus is the leading market intelligence platform for key decision makers. We power some of the world’s most well-respected institutional investors, corporations, and consultancies through the largest and most comprehensive database of primary and market information. Our products and services enable clients to discover unmatched insights and answers to the most challenging questions they face to help them make better informed decisions. (And because a job description can only contain a fraction of how we operate, click here to learn more about the Tech Team at Tegus!)
As a senior machine learning engineer at Tegus, your job will be to build product features powered by machine learning on top of our unique, proprietary datasets. The core of this data is an ever-growing set of “expert interviews”--primary research conversations between financial analysts and domain experts, arranged by Tegus, who discuss the ins-and-outs of a particular company’s business. In 2021, Tegus acquired BamSEC, adding a comprehensive database of SEC filings and earnings/events transcripts to the platform. And last year, through our acquisition of Canalyst, we added custom financial models and cleaned financial time series data.
Because so much of this data is unstructured text, your work will lean heavily towards NLP and large language models. While we make extensive use of OpenAI API’s, we plan to explore other vendors, future open source models, and perhaps even custom-trained or fine-tuned models.
As a team, we have already launched LLM-powered transcript summaries and a search/browse experience based on topic extraction. A main focus of our upcoming work will be a chat agent for financial professionals that has access to all of our underlying datasets.
Our work is core to the future of the company. You will join as one of the first hires, reporting to the VP of Machine Learning, and will help to set the culture and practice of how we do machine learning at Tegus. You will also get to work on real business problems using some of the latest and most exciting tools and methods in the industry.
As a senior machine learning engineer at Tegus, your job will be to build product features powered by machine learning on top of our unique, proprietary datasets. The core of this data is an ever-growing set of “expert interviews”--primary research conversations between financial analysts and domain experts, arranged by Tegus, who discuss the ins-and-outs of a particular company’s business. In 2021, Tegus acquired BamSEC, adding a comprehensive database of SEC filings and earnings/events transcripts to the platform. And last year, through our acquisition of Canalyst, we added custom financial models and cleaned financial time series data.
Because so much of this data is unstructured text, your work will lean heavily towards NLP and large language models. While we make extensive use of OpenAI API’s, we plan to explore other vendors, future open source models, and perhaps even custom-trained or fine-tuned models.
As a team, we have already launched LLM-powered transcript summaries and a search/browse experience based on topic extraction. A main focus of our upcoming work will be a chat agent for financial professionals that has access to all of our underlying datasets.
Our work is core to the future of the company. You will join as one of the first hires, reporting to the VP of Machine Learning, and will help to set the culture and practice of how we do machine learning at Tegus. You will also get to work on real business problems using some of the latest and most exciting tools and methods in the industry.
Responsibilities
- Collaborate with product managers and product engineers to prototype, build, and release features in the Tegus Platform that leverage the latest advances in machine learning applied to our proprietary dataset of financial text.
- Write production python code in our internal machine learning packages and deploy production microservices.
- Stay on top of the latest advances in machine learning, including reading and presenting research papers.
- Influence how we architect and deploy our machine learning code and services.
- Mentor and pair with one or more junior ML engineers.
Qualifications
- Bachelor’s degree in a quantitative discipline or demonstrated experience working on data-intensive problems. (Preferred: Masters or PhD).
- 5 years of experience working in a data-intensive or machine learning role, with at least 2 of those years in an industry role.
- Demonstrated experience training and deploying machine learning models with a preference towards NLP applications.
- Deep experience in the python data and machine learning ecosystem, including experience with pytorch.
- Familiarity with docker, python API frameworks like FastAPI, and software engineering best practices (preferred: Previous experience deploying microservices on kubernetes).
- Practical, iterative, product-focused mindset over slower, methodical, research-minded approach.
Benefits & Perks
- Comprehensive medical, dental, and vision plans.
- 401K plan with an employer match.
- Paid parental leave for all parents.
- Unlimited paid vacation, flexible work hours, and 10 observed paid holidays per year.
- Employer funded long-term disability.
- Award-winning culture with regular team-wide events designed to foster connections and promote creativity.
- Generous employee referral bonus program.
- The opportunity to attend peer-nominated quarterly DEI events.
- Working for a thriving, performance-based company that values promoting from within, career advancement and transparency.
- Work from our state of the art office in the heart of Chicago’s Loop featuring standing desks, nursing parent rooms, gender neutral bathrooms, subsidized gym access, and full amenity floor.
- Commuter benefits & a fully stocked kitchen with rotating snacks and beverages.
#LI-Hybrid
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