Architect full machine learning products with our cross-functional teams...
Working at Thinking Machines
Thinking Machines is a technology consultancy building AI & data platforms to solve high impact problems for our clients. Our vision is for Southeast Asia to become a global hub for data science. To do that, we create data cultures one organization at a time.
We’re a company made up of intellectually curious, civic-minded, forever-learning individuals. We believe that great data science products are built with care for people, and that the best way to drive inclusive innovation is to start with a diverse team.
Our field of work is incredibly dynamic, so we want to work with people who are committed to growing with us. We want to hire people who can demonstrate an ability to learn, then provide them with personalized coaching, growth opportunities, and a great working environment to get them to world-class.
This is an opportunity for someone with a strong portfolio of work in machine learning to do great work in the company of a high-performance team. This job demands creativity, critical thinking, and a focus on delivering excellent work. You’ll be expected to effectively handle projects from day one, and will be provided with effective guidance as you learn and implement machine learning methods for our clients and internal products.
We’re a growing startup with constantly evolving responsibilities, and the following is an incomplete but representative list of things you can expect to be doing:
- Developing machine learning models: feature engineering, experimenting with different model types, choosing the right metrics and measuring performance, hyperparameter tuning, feature importance, etc.
Exploring data and its sources: looking for patterns and signals in the data, identifying important fields, gleaning insights, and discerning whether machine learning can even apply to the problem
Understanding model design and decisions: explaining how models work under the hood and how a model arrived at a certain prediction, choosing the right model family, and justifying accuracy tradeoffs for faster performance
Research and keeping up with the tech space: reading through published ML papers, and implementing improved versions of their models in new domains
Acquiring, cleaning, and evaluating the integrity of datasets! Let’s be real, this is a tricky and satisfying 25% of the job. We use Google Cloud Platform for many components of our machine learning workflow.
In addition, senior ML Researchers are also expected to assume technical leadership roles. They must be able to conduct literature reviews, write technical papers, and deliver model roadmaps. They must be able to offer sound technical guidance to junior staffers and the rest of the project team members.
We’re looking for someone who meets the following profile:
- Comfort with machine learning models - You have a demonstrated understanding of classic machine learning models for classification and regression (e.g. decision trees, ensemble models, SVMs etc). Applicants who are aiming for more senior positions in this role must have advanced knowledge in at least one specific area. Here are some rough categories:
- Sequential Prediction Models (e.g. time series forecasting, LSTMs etc)
- Computer Vision (e.g. CNNs, SSDs etc.)
- Language Models (e.g. word embeddings, text representations, etc)
- Comfort with code - You can use your local machine to scrape, load, and parse through moderately large datasets without much handholding.
- Clear communication - We help clients get the most out of their data, so we diagnose their needs effectively, do the analysis correctly, and communicate our findings in a way that leads to understanding and action. At minimum, you need to have the ability to articulate your points logically, and have to be willing to learn this skillset as you grow with us.
- Productive curiosity - You ask a lot of the right questions. Find a surprising correlation? Dig into the raw data to validate it.
- Enjoys both teaching and learning - We believe that data science is an incredible field to be in today. There’s a huge amount of new material to learn, we all want to learn it, and we’re looking for someone who wants to contribute to everyone’s growth. As part of our job interview, we’ll be asking you to read and summarize a machine learning paper for us.
- Strong sense of initiative—You’re always looking for ways to be useful and you hate having nothing to do.
- Social intelligence— It’s extremely important that you work well with others and thrive in an environment with lots of teamwork and interpersonal interaction.
Additionally, we are requiring Philippine candidates to have an internet connection speed of at least 12 mbps and a viable work from home setup as we are now operating as a fully remote company.
Qualifications and Competencies
- Undergraduate/Graduate degrees in Computer Science, Physics, Mathematics, Statistics, or any related field, OR relevant work experience
- Strong fundamental statistics skills, and linear algebra handling skills
- Strong quantitative analysis skills
- Familiarity with statistical programming languages like Python, or R
- Bonus Points (You’re not expected to have all the below qualifications but competitive candidates have at least two):
- Knowing the scientific Python toolkit, and TensorFlow + Keras
- Publications in peer-reviewed journals and conferences
- Comfort with cloud platforms (AWS or GCP) for training machine learning models on >10GB datasets
- Domain expertise in a non-tech field. Are you an expert in energy, finance, insurance? Bring something to the table that we don’t yet have!
- Fluency with the open source frameworks and good software engineering practices
Benefits and Perks
We offer the following compensation and benefits:
- Competitive salary — the compensation amount is positively correlated with the difficulty and scope of the job, relevant experience, fit, and skill factors.
- Fully remote — due to the global pandemic, we have shifted to a fully remote company for the foreseeable future while we monitor the situation.
- Individual professional development budget — an annual budget for conferences, training courses, books, and software are available to sharpen your skills and build new ones to help you grow in your role.
- Full health benefits — generous health insurance package.
- Regular 1:1 meetings with the leadership team to discuss career and personal goals, job progress and any questions and concerns.