July 2, 2024
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Warsaw, Mazowieckie, Poland, Poland
July 2, 2024
Apply NowJob description
ALGOTEQUE is an IT consultancy firm that helps startups, mid-sized and large corporations to create and deliver innovative technologies.
Our team has a successful track record in designing, developing, implementing, and integrating software solutions (AI, ML, BI, Web, Automation) for Telecom, Energy, Bank, Insurance, Pharma, Automotive, Industry, e-commerce. We deliver our services both in fixed-price and time-and-materials models, helping our customers achieve their business and IT strategies.
Job Description
Algoteque is seeking a talented Data Scientist / ML-Engineer to join our dynamic team. This role involves working on innovative projects for our clients, focusing on deep learning, model optimization, and production deployment.
Responsibilities
Deep Learning: Utilize deep learning techniques for tasks such as image, text, and video classification using neural networks.
Model Development: Collaborate with the team to develop, train, and research new and existing machine learning models.
ML-Ops: Implement and maintain ML-Ops practices to ensure models are effectively brought into production.
Data Science Ecosystem: Utilize the Python data science ecosystem, including tools like pandas and numpy, to analyze and manipulate data.
Feedback Loops: Develop and implement feedback loops to generate new training data as part of the machine learning lifecycle.
Best Practices: Apply best practices in machine learning and data science to ensure robust and reliable models.
Profile / Requirements
Deep Learning: Experience with deep learning frameworks such as PyTorch and Tensorflow.
Python: Proficiency in Python and familiarity with its data science ecosystem, including pandas and numpy.
Statistics: Solid foundations in statistics to support data analysis and model validation.
ML-Ops: Experience in ML-Ops, including bringing models into production and maintaining them.
Production Models: Proven experience in implementing and optimizing machine learning models for production environments.
Problem-Solving: Strong problem-solving skills and the ability to work independently on complex tasks.
Preferred Qualities
Innovative Thinker: Ability to think creatively and propose innovative solutions to complex problems.
Team Collaboration: Strong collaboration skills to work effectively with other team members and stakeholders.
Continuous Learning: Commitment to staying updated with the latest developments in machine learning and data science.
What We Offer
Innovative Projects: Opportunity to work on cutting-edge projects for leading clients.
Professional Growth: Continuous learning and development opportunities.
Flexible Work Environment: Remote work.
If you are a dedicated Data Scientist / ML-Engineer with a passion for deep learning and model optimization, we would love to hear from you.
AO2901
Our team has a successful track record in designing, developing, implementing, and integrating software solutions (AI, ML, BI, Web, Automation) for Telecom, Energy, Bank, Insurance, Pharma, Automotive, Industry, e-commerce. We deliver our services both in fixed-price and time-and-materials models, helping our customers achieve their business and IT strategies.
Job Description
Algoteque is seeking a talented Data Scientist / ML-Engineer to join our dynamic team. This role involves working on innovative projects for our clients, focusing on deep learning, model optimization, and production deployment.
Responsibilities
Deep Learning: Utilize deep learning techniques for tasks such as image, text, and video classification using neural networks.
Model Development: Collaborate with the team to develop, train, and research new and existing machine learning models.
ML-Ops: Implement and maintain ML-Ops practices to ensure models are effectively brought into production.
Data Science Ecosystem: Utilize the Python data science ecosystem, including tools like pandas and numpy, to analyze and manipulate data.
Feedback Loops: Develop and implement feedback loops to generate new training data as part of the machine learning lifecycle.
Best Practices: Apply best practices in machine learning and data science to ensure robust and reliable models.
Profile / Requirements
Deep Learning: Experience with deep learning frameworks such as PyTorch and Tensorflow.
Python: Proficiency in Python and familiarity with its data science ecosystem, including pandas and numpy.
Statistics: Solid foundations in statistics to support data analysis and model validation.
ML-Ops: Experience in ML-Ops, including bringing models into production and maintaining them.
Production Models: Proven experience in implementing and optimizing machine learning models for production environments.
Problem-Solving: Strong problem-solving skills and the ability to work independently on complex tasks.
Preferred Qualities
Innovative Thinker: Ability to think creatively and propose innovative solutions to complex problems.
Team Collaboration: Strong collaboration skills to work effectively with other team members and stakeholders.
Continuous Learning: Commitment to staying updated with the latest developments in machine learning and data science.
What We Offer
Innovative Projects: Opportunity to work on cutting-edge projects for leading clients.
Professional Growth: Continuous learning and development opportunities.
Flexible Work Environment: Remote work.
If you are a dedicated Data Scientist / ML-Engineer with a passion for deep learning and model optimization, we would love to hear from you.
AO2901
