4+
Experience
Remote
Job Type
B2+
English Level
Who We’re Looking For
Jaxel is seeking a Data Scientist with extensive Machine Learning Engineering expertise to join our cutting-edge team.
What You’ll Do
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Analyze large-scale structured and unstructured datasets using statistical methods and visualization tools.
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Design, implement, and optimize scalable ML pipelines for various applications.
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Train and fine-tune Deep Learning architectures like Transformers and Graph Neural Networks.
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Develop and integrate self-hosted Large Language Models (LLMs), including embedding generation.
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Utilize PyTorch framework extensively for model development and deployment.
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Work within Big Data ecosystems (Hadoop, Apache Spark) for distributed processing and analysis.
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Perform distributed training and inference across multiple nodes or clusters.
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Collaborate closely with cross-functional teams during architecture planning and implementation phases.
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Stay abreast of emerging trends and advancements in AI/ML technologies.
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Participate actively in technical discussions, ideation sessions, and decision-making processes related to system architecture.
What You’ll Need
What We Offer
- Competitive salary.
- Remote work opportunity.
- Comfortable work in your local time zone.
- Flexible work schedule.
- Professional growth and development.
- Multicultural working environment.
Strong background in mathematics/statistics and computer science fundamentals.
Proficiency in Python programming language along with relevant libraries (NumPy, Pandas, Scikit-Learn).
In-depth knowledge of Deep Learning concepts and frameworks (TensorFlow/Keras/PyTorch).
Hands-on experience working with Big Data platforms (Hadoop/YARN/HDFS/S3/Azure Blob Storage etc.).
Expertise in distributed computing paradigms via Apache Spark or similar systems.
Familiarity with containerization technologies (Docker/Kubernetes) preferred but not mandatory.
Comfortable collaborating effectively within diverse team environments.
Willingness to continuously learn new methodologies, tools, and best practices.