Актуальные заказы по Data Modeling

Lead ML Engineer

Удаленно
Full-time

Responsibilities 

• Evaluate and adapt state-of-the-art machine learning (ML), computer vision (CV), generative AI, and time series forecasting algorithms to meet product and client objectives. 

• Research, design, and implement innovative ML algorithms for image, video, multimodal, and temporal data. 

• Architect and develop full-stack ML pipelines—from data acquisition and preprocessing to training, evaluation, and deployment in cloud (AWS) or edge environments. 

• Prototype and validate proof-of-concept (POC) solutions for vision, generative AI, and time-series forecasting problems. 

• Translate customer requirements into actionable tasks, ensuring a clear understanding of objectives, scope, and expected outcomes. 

• Analyze structured and unstructured data to uncover trends, patterns, and anomalies. Apply ML and statistical methods for prediction and forecasting. 

• Prepare detailed technical documentation, reports, and presentations for internal and external stakeholders. 

• Communicate complex technical topics effectively to both technical and non-technical stakeholders, including clients and business partners. 

• Lead projects from prototype to production, ensuring scalability, reliability, and performance of solutions. 

• Contribute to internal software development processes and team collaboration initiatives. 


Requirements 

• Strong hands-on experience in delivering ML solutions, including production-grade computer vision and forecasting models. 

• Proven expertise in forecasting and time series data handling (e.g., ARIMA, LSTM, temporal convolutional networks). 

• Proficiency in image and video processing, including segmentation, pose estimation, object detection, and multimodal data fusion. 

• Experience with generative AI models such as diffusion-based text-to-image/video, multimodal LLMs, and prompt engineering. 

• Skilled in reading, interpreting, and applying insights from academic research papers. 

• Expertise in deep learning frameworks like PyTorch or TensorFlow. 

• Strong object-oriented programming skills with clean, production-quality Python code.

• Familiarity with Vision Transformers (ViTs), especially for action recognition, object tracking, and video understanding tasks. 

• Cloud deployment experience, particularly with AWS. 

• Excellent communication skills in English (C1 or higher), both written and spoken. 

• Strong ability to work independently, prioritize tasks, and manage multiple projects simultaneously. 

Nice to Have 

• Master’s or Ph.D. degree in Machine Learning, Computer Science, Mathematics, or a related field.

• Contributions to open-source ML or CV libraries or participation in Kaggle competitions.

Senior ML/CV Engineer

Удаленно
Full-time

Company published in 1997, was built from the ground up to specialize in new product development and R&D, tackling the most difficult problems in the tech sphere. Now company expanded to offer early-stage innovation and ideation plus digital transformation business consulting. Company's superpower is to deliver all of this under one roof on a global scale.


Responsibilities:

• Design, develop computer vision systems and systems for video analysis.

• Prototype proof-of-concept (POC) solutions for specific computer vision and machine learning problems to validate ideas.

• Lead projects from prototype to production.

• Identify and resolve performance and scalability issues.

• Actively participate in the team’s software development processes.


Requirements:

required experience 5+ years

• Strong experience in computer vision. Hands-on involvement in the development of multiple Computer Vision projects that have been deployed to production.

• Strong foundational understanding of Machine Learning concepts and how they apply to Computer Vision tasks.

• Strong expertise in processing and analyzing image and video data.

• Hands-on experience developing and fine-tuning models for segmentation, pose estimation, and object detection.

• Proficiency with deep learning frameworks such as PyTorch and TensorFlow.

• Excellent object-oriented programming skills, with the ability to write high-performance, production-quality code in Python.

Proficient in English for effective communication.


Start Date:

  • As soon as possible (subject to a thorough review and interview process by Softeq and the client).


Location:

  • 100% remote work; must have the ability to work overlapping hours with Eastern Standard Time (EST).

Data Science Team Leader

Удаленно
Full-time

The project - a platform for creating and publishing content on social media using artificial intelligence tools is looking for a  Data Science Team Leader with a focus on generative models (m/f).


Responsibilities:

— Study and transform data science prototypes.

— Research and implement appropriate ML algorithms and tools.

— Design machine learning systems.

— Develop machine learning applications according to requirements.

— Know the SOTA in the field of generative technologies and be able to reproduce key experiments.

— Develop prototypes based on generative models for multimodal content (text, images, video).

— Develop and implement a pipeline of product integration for successful prototypes.

— Manage a team of machine learners to plan, implement and support new technologic solutions.

— Understand how certain product features impact business results.


Requirements

— Previous experience efficiently conducting research and creating ad hoc generative prototypes.

— Previous experience in the management of RnD teams.

— A strong background in probability theory and statistics, data mining, and machine learning.

— Proficiency in Python and proven experience using popular ML packages (PyTorch, TensorFlow, huggingface,etc).

— Deliver your work to production as a stand-alone microservice.

— Be enthusiastic about DS and stay up to date with SotA Machine Learning algorithms and developments.

— Be eager to help your teammates, share your knowledge with them, and learn from them.

— Be able to write production code.

— Be open to receiving constructive feedback.

— Academic papers at major ML conferences is a plus.

— Experience as a CTO in a start-up is a plus.