Machine Learning Engineer @

2 tygodni temu

Warsaw, Polska Appsilon Pełny etat

About Appsilon

Appsilon is an ambitious and fast-growing software house and consultancy specializing in machine learning and action support systems with Fortune 500 clients across the globe.

Our unique company is inspired by a mission to improve our society and environment.

We have a growing focus on Life Sciences, including drug development enhancement, boosting molecular biology research, health-care-related topics, and biodiversity preservation.

We have a strong team of Machine Learning experts and have delivered long-term research & development projects and quick proof of concepts.

We work with enterprises, startups, and academic partners.

As Appsilon, we are also a global leader in R and Shiny, which are used by companies of all sizes to build data applications.

When companies encounter difficult problems or want to initiate large-scale enterprise projects, they come to us.

Your Role as a Machine Learning Engineer

Regular duties will include:
Preparing data
Collect data from source (facilitate a transfer of a large static dataset or connect to a live database source)
Transform data to prepare for modeling (e.g., resize images, convert formats, obtain labels)
EDA - exploratory data analysis
Understand relevant data properties Statistics (e.g., class distributions in the proposed train-test split are skewed)
Data issues (e.g., images taken at night of fast-moving objects are blurred)
Dataset characteristics (similarities and differences with known datasets)
Visualize the findings
Modeling
Pick or design appropriate model architecture
Pick or define a custom set of losses
Run, monitor, and track models' training Investigate models' performance, identify strong and weak points
Working by software engineering standards
Make sure the data and modeling pipelines are modular and reproducible
Write code that can easily be returned to and reused in new contexts
Pipeline setup and improvements
Setup cloud infrastructure needed for data storage, modeling, and serving the models)
Setup and help maintain MLOps practices
Use known and new tools to meet project requirements
Handle meetings with clients
Effective communication at both technical and stakeholder levels
Ability to drill down on client needs and pain points to collect or refine project requirements
Present at conferences, meetups, webinars
Some technical-expert-type involvement in sales
Assisting sales in making a good technical impression by asking the right technical questions to prospective clients
What's in it for you?

Competitive salary :

Enjoy a monthly B2B salary of 14, ,000 PLN / 3,600-5,400 USD + VAT, based on a full-time commitment.

Generous paid time off:

Benefit from 26 days of paid holidays, plus the equivalent of public holidays in Poland, estimated at 13 days in 2024.

Comprehensive sick leave:
Receive 33 paid sick days per year at 80% of your salary.

Professional Development Budget:

You'll have a 5% addition to your salary allocated to a Professional Development Budget for activities that help you grow.

Flexible remote work:
Embrace remote work with flexible hours tailored to your time zone and family life.

Training and conferences:
Enjoy four paid days per year for training, conferences, events, or workshops.

Health benefits:
Access private health care insurance (in Poland) or a cash equivalent if you're not in Poland.

Fitness perks:
Receive a FitProfit or FitSport membership card (in Poland) or a cash equivalent if you're not in Poland.

Life insurance:
You and your family will be covered with life insurance.

Personal assistant:
Benefit from AskHenry, your assistant.
What can you expect during the recruitment process?
Interview with the Recruiter (with a live task assignment)
Home assignment
2 Interviews with the members of the ML Team
Offer

Must-have Requirements:
2+ years of experience in a similar role
Hard skills
Great software engineering background
Extensive Python knowledge
Experience with PyTorch
Experience in data wrangling
Experience with machine learning pipelines and experiment reproducibility
Knowledge of MLOps practices
Understanding of advanced machine learning (multi-modal training, the influence of batch preparation on training, learning rate schedule, leveraging feature maps for new tasks, etc.)
Experience in classical machine learning (e.g., tree-based models) as well as deep learning (e.g., computer vision)

Nice to have:
Interest or experience in ML applied in Life Sciences
Public projects (public repositories, profile on Kaggle-like sites/history of hackathons, etc.)
Interest or experience in Data4Good (especially contribution to healthcare/drug discovery and climate crisis/biodiversity preservation)
History of academic papers (ML or domain-specific)
History of public speaking (conference talks, seminars, teaching)
Importantly, knowledge of R is not a requirement. It can be useful in collaborations with the Applications team at Appsilon.
Soft Skills
Trained analytical thinker
Able to switch between a hacker mentality of getting things to work and an organized engineer adhering to basic principles when refactoring or building key pipeline elements
Able to abstract from technical issues and communicate also on a high level (not only how we do things, but why we do them)
Know your limits - able to spot when it is time to ask others for help
Very good English (at least C1) - we work exclusively in English
Personal traits
Independent , yet willing to closely collaborate
Reliable , high standards, organized
Curious in ML topics
Open to remote work, like remote-first working culture
About Appsilon