Viseven
AI/ML Architect
Job Description
The rapidly expanding team includes more than 700+ highly-skilled tech- and non-technical experts: front- and back-end developers, BA specialists and managers who create, localize and customize applications at 8 offices: in Kyiv, Zhytomyr, Vinnytsia, Ternopil (Ukraine), Tallinn (Estonia), New Delhi (India) and Bridgewater (NJ, USA).
Responsibilities:
- Understand business objectives and developing models that help to achieve them, along with metrics to track their progress
- Understand and use computer science fundamentals, including data structures, algorithms, computability and complexity and computer architecture
- Analyse the ML algorithms that could be used to solve a given problem and ranking them by their success probability as well as analyse large, complex datasets to extract insights and decide on the appropriate technique
- Build algorithms based on statistical modelling procedures and build and maintain scalable machine learning solutions in production
- Apply machine learning algorithms and libraries
- Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
- Verifying data quality, and/or ensuring it via data cleaning
- Supervising the data acquisition process if more data is needed
- Finding available datasets online that could be used for training
- Training models and tuning their hyperparameters
- Analyzing the errors of the model and designing strategies to overcome them
- Manage the infrastructure and data pipelines needed to bring code to production, deploying models to production
- Provide support to engineers and product managers in implementing machine learning in the product.
- Collaborate with data engineers to build data and model pipelines
- Liaise with stakeholders to analyse business problems, clarify requirements and define the scope of the resolution needed
- Develop machine learning applications according to requirements
Requirements:
- Proven experience as a Machine Learning Engineer or similar role
- Understanding of data structures, data modelling and software architecture
- Deep knowledge of math, probability, statistics and algorithms
- Demonstrated technical expertise around architecting solutions around AI, ML, deep learning and related technologies.
- Experience with Amazone Cloud and AWS AI services
- Developing AI/ML models in real-world environments and integrating AI/ML using Cloud native or hybrid technologies into large-scale enterprise applications.
- In-depth experience in AI/ML and Data analytics services offered on Amazon Web Services and/or Microsoft Azure cloud solution and their interdependencies.
- Experience in effective data exploration and visualization (e. g. Excel, Power BI, Tableau, Qlik, etc. )
- Familiarity with machine learning frameworks and libraries
- Excellent communication skills
- Ability to work in a team
- Outstanding analytical and problem-solving skills
- The ability to explain complex process to people who aren’t programming experts
- English – upper-Intermediate and higher
- Previous experience in communication with clients, ability to interact with clients freely, and consult them from a technical standpoint.
- Pharma domain background
What we provide:We understand that our team members are essential to making our goals a reality, so we value and empower them to share their vision. And we reward this kind of passion with highly competitive compensation and exceptional benefits, such as:· Competitive compensation and regular performance based salary and career development reviews· Passionate experienced team, friendly atmosphere· Professional and career growth· Paid time off – 18 business days per year (20 business days after 2 years of cooperation) + national public holidays· Non-documented sick leave – 4 business days per year· Documented sick leave – 20 business days per year· Family leave – 3 paid business days in case of marriage, childbirth or bereavement· English learning courses· Opportunities to participate in professional forums and conferences· Regular corporate events and team-buildings· Enjoyable working environment: comfortable and fully equipped office and possibility to work from home