Careers

Careers

Bring your perspective to the team

Open Positions

Deep Learning Engineer

Experience level: 4+ years of ML research or engineering

Location: Anywhere in Portugal. We encourage team members to work both on-site and remotely, as they see fit. We provide access to on-site offices in Porto and Lisbon. See section on Locations for more details.

What we offer:

  • Competitive salary + bonus (adjusted according to experience and achievements)
  • Flexible and fast-paced environment
  • 35-hour work week
  • 25 days of Holidays
  • Personal development tools: access to books, publications, mentors
  • Team retreats in very cool locations
  • Other agreed tailored benefits to your needs

Fluency with:

  • Deep Learning, with particular focus on sequence models (LSTMs, Transformers, etc) and Graph Neural Networks
  • Training and fine-tuning large models
  • One or more DL frameworks: Tensorflow, PyTorch or JAX
  • Python, Git/GitHub

In addition, the following skills are valued, but not strictly required:

  • Previous contact with ML tools and platforms to run experiments at scale (e.g. Ray)

The role:

You will be part of a team applying advanced Deep Learning techniques to fundamental problems in Molecular Biology. This can involve dealing with genetic or proteomic datasets, creating ML models that process sequential data about genes and proteins, model their 3d geometry as well as interactions they establish among themselves and with different molecules. You will make use of concepts from Geometric Deep Learning, such as Graph Neural Networks, and try to incorporate physical, geometric and evolutionary priors with other sources of experimental data, into an end-to-end learning architecture.

In this position, you will be spending a lot of your time modeling Biology problems from the perspective of Machine Learning. You will not be alone in this challenge. You will interact with people of different backgrounds, ranging from Computer Science, Mathematics, Physics, to Biology experts. The kind of work you will be doing involves a lot of ML exploration and experimentation. We will be trying to keep the cycle idea-implementation-experiment as agile as possible, by having clear metrics and good ML infrastructure and best-practices in software engineering.

What will help you to do your job well:

  • People person - You love to interact and build relations with people, you really care deeply about them and you will do your best to make them successful.
  • Strategic thinker - You always try to connect the dots to see the big picture. You are great at prioritizing the high impact things. When you execute, you make a plan first, but you are flexible to change it according to new information.
  • Love of Learning - Learning new things brings you excitement and fulfillment.
  • Trusted advisor - You’re a great listener, confident and advisor at the same time.

Other things that will improve your application:

  • Relevant research articles where you were a co-author
  • Public GitHub repositories with your own projects
  • Technical blog posts, tutorials or recorded talks
  • Certificates of online courses related with Deep Learning (e.g. from Coursera)

ML Ops Engineer

Experience level: 2+ years of ML Ops (4+ years of ML-related experience in total)

Location: Anywhere in Portugal. We encourage team members to work both on-site and remotely, as they see fit. We provide access to on-site offices in Porto and Lisbon. See section on Locations for more details.

What we offer:

  • Competitive salary + bonus (adjusted according to experience and achievements)
  • Flexible and fast-paced environment
  • 35-hour work week
  • 25 days of Holidays
  • Personal development tools: access to books, publications, mentors
  • Team retreats in very cool locations
  • Other agreed tailored benefits to your needs

Fluency with:

  • Using one or more DL frameworks: Tensorflow, PyTorch or JAX
  • Training models using hardware accelerators at scale: GPUs or TPUs
  • Using Cloud computing infrastructure (Google Cloud, AWS, or Azure)
  • Creating and managing Docker containers
  • Implementing distributed systems for ML training and performing hyper-parameter optimization at scale (e.g. using frameworks as Ray)
  • Building, maintaining and administering computational infra-structures composed of clusters of local machines (CPU+GPU)
  • Building data pipelines for producing, managing and converting training data to/from various formats (e.g. json, tfrecords)

In addition to those, the following experience would be valued:

  • Track record of supporting ML research teams
  • Dealing with checkpointing and preemptible virtual machines (e.g. spot instances)
  • Logging and visualizations frameworks (e.g. TensorBoard, Weights and Biases, Neptune or others)
  • Experience in developing and maintaining ML Leaderboards (e.g. Kaggle-style)
  • Deploying ML models to a cloud API

The role:

You will be part of a team of Deep Learning researchers and engineers, tackling fundamental problems in science. Your main goal will be to help accelerate the speed at which we conduct research and innovation. You are expected to build and develop tools and infrastructure that should have a multiplicative impact on the productivity of the entire team. This will involve building and supporting experiment infra-structures such that our ML models can train faster as we increase our computational resources, as well as building all the tooling such that the research we produce is reproducible (save hyper-parameters and config files used, experimental logs, model checkpoints, etc.). You will also be responsible for setting up or building the tools that enable us to do better tracking and management of experiments, including leaderboards and visualizations frameworks.

What will help you to do your job well:

  • People person - You love to interact and build relations with people, you really care deeply about them and you will do your best to make them successful.
  • Strategic thinker - You always try to connect the dots to see the big picture. You are great at prioritizing the high impact things. When you execute, you make a plan first, but you are flexible to change it according to new information.
  • Love of Learning - Learning new things brings you excitement and fulfillment.
  • Trusted advisor - You’re a great listener, confident and advisor at the same time.

Other things that will improve your application:

  • Relevant research articles where you were a co-author
  • Public GitHub repositories with your own projects
  • Technical blog posts, tutorials or recorded talks
  • Certificates of online courses related to ML, cloud computing, infrastructure (e.g. from Coursera)

Hardware Engineer

MEng in Electrical Engineering, Electronics or similar.

Engineering Experience: 4+ years

Location: anywhere in Portugal. (see section on Locations for more details)

In this role you will work in close collaboration with your colleagues to identify computational bottlenecks in various projects and propose FPGA-based solutions that other team members can use in a plug-and-play fashion. You will be contributing to the R&D infrastructure at Inductiva that will allow us to go from an idea of how to speed-up a certain computational stage, to prototype an accelerator, and finally to a production-level solution that we can deploy both internally and externally to our partners.

Your day-to-day might be quite diverse, and include things like educating the team on hardware design and architecture, or just spending some time reading papers and studying background material from Maths/Physics/ML to sharpen your skills and expand your knowledge.

To give you a flavour of the type of work you will be developing at Inductiva, here are some links to interesting resources and prior work by other groups:

Technologies:

  • Programming languages: VHDL, Verilog and Python
  • FPGAs: Xilinx
  • Source control: Git
  • Operating Systems: Linux / MacOS

Send us your CV & Cover Letter

Spontaneous Application

MSc or PhD in Mathematics, Physics, Computer Science or Engineering

Research Experience: early career

Location: anywhere in Portugal. (see section on Locations for more details)

We are currently not in need of filling up a “vacancy” for a specific role or project, but we are always looking for highly motivated candidates that have a solid scientific or engineering background. If you think you would be a great fit for Inductiva we invite you to start a conversation with us.

In this role, you will be applying Machine Learning methods to problems in Physics or Mathematics. This should provide you an opportunity to use your scientific background while developing your skills in Machine Learning and contributing to the broader research efforts of the entire team.

Your work may involve: designing algorithms that search for solutions in large combinatorial spaces using pattern recognition techniques and/or training neural networks capable of solving partial differential equations. There are many promising directions in this field that may benefit from Deep Learning methods.

To give you a flavour of the type of work we aim to develop at Inductiva, here are some links to interesting papers by other groups:

  • Machine Learning for Combinatorial Optimization, arXiv:1811.06128
  • A deep learning algorithm for solving partial differential equations, arXiv:1708.07469
  • Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations, M. Raissi et al., JCP 2019

You won’t need to be an expert in ML from the beginning, as you will be part of a team with ML researchers that will provide guidance, time and support for you to learn.

Send us your CV & Cover Letter

We are looking for people of diverse backgrounds, to build a team where we can all learn from each other. We want to forge a truly inclusive culture right from the beginning, so we encourage applications from under-represented groups in science and engineering.

At Inductiva, you will enjoy a great deal of flexibility and freedom to explore different topics. We want everyone in the team to grow as a person and become a better scientist, so that we can tackle bigger problems together. If you are applying for a junior role, we will provide all the guidance you might need, but we promise not to micromanage you!

Also, we understand you may want to dedicate more time to your personal life. Therefore, at Inductiva, all positions have part-time options that we can tailor to your needs.

We are committed to operating at high ethical standards. This means we will not work on developing applications that reinforce existing social biases, increase pressure on the environment or that can be used to cause harm in general. Also, aligned with our broader research mission, we are committed to sharing our results via publications and open-source code.

Inductiva has been designed from inception to operate distributedly. We encourage team members to work both on-site and remotely, as they see fit.

We currently have offices in:

  • downtown Lisbon, at Rua da Prata 80, where we are part of the Startup Lisboa business incubator community.
  • downtown Porto, at Rua dos Bragas 208.

If there is no pre-established Inductiva office in your city and you wish to work outside your own home, we will arrange for a good co-working space near you.

What is important for us is that you have access to a place where you feel comfortable, with a good infrastructure that makes it easy to collaborate with colleagues and where you can control the amount of distractions you are exposed to.

Our compensation packages are composed of two components: a base salary, which is indexed to your scientific seniority, and a variable component contingent on the achievement of certain goals and milestones.

If you recently completed your master degree (MEng, MSc) and you are just starting your research career, working with us will somewhat resemble doing a PhD (only better, we hope!). As such, your base salary will be approximately what you would get from a PhD grant from "Foundation for Science and Technology" (FCT), in Portugal.

If you are a more senior candidate (e.g. hold a PhD and/or have several years of equivalent work experience), you will divide your time at Inductiva between research and mentoring tasks, in order to maximize your impact. Your compensation will be defined based on your specific profile and experience.

In addition to the base salary, our compensation packages include monetary bonuses to be offered when you achieve certain goals and milestones that are in agreement with our broader mission and philosophy. For example, at Inductiva we can offer cash bonuses upon:

  • publishing a preprint on arXiv;
  • getting a paper accepted at a good conference;
  • open-sourcing your code;
  • giving a talk at a local meetup;
  • writing a post about your research in our company blog;
  • completing a relevant course on Coursera.

As a reference, we hope to be able to attribute annual bonuses of up to 20% of a full-time base salary. More detailed rules and guidelines for bonuses will be provided and discussed internally with the team.

We believe it is not so much about the time you put in, but about how productive you can be with the time you have available. We want you to have the best possible conditions for you to contribute to the team.

When you start at Inductiva, we will provide you a good laptop (a MacBook Air, or an equivalently priced Linux-based laptop) and a good external monitor (e.g. 27 inches Full HD), such that you can enjoy the lightweight mobility when you need it, as well as enough screen space while you are at your desk. For computational intensive tasks, such as running large scale Machine Learning or Optimization experiments, we will give you access to a cloud computing platform (e.g. Google Cloud, AWS or Azure).

If you are regularly working from home and you need to improve your working area (e.g. desk, chair), or you need better video-conferencing material (e.g. webcam, micro, light), we can help you with that, so that you can collaborate with the rest of the team without glitches and waste of time!

Inductiva nurtures a diverse and inclusive workplace. We are committed to developing people regardless of gender, nationality, religion, age, sexual orientation or background. We aim at interacting with our community and partners with open-mindedness and respect.

Because we are aware this is an enduring challenge, we count with the support and guidance of our D&I partner, FairHQ.