Machine Learning Engineer
Serbia - Remote
Acumatica
Acumatica Cloud ERP provides the best business management solution for transforming your company to thrive in the new digital economy.Acumatica is a leading company in the cloud ERP area, which creates software that empowers small and mid-size businesses in order to unlock their potential and drive growth. Built on the world’s best cloud and mobile technology and a unique customer-centric licensing model, Acumatica delivers a suite of fully integrated business management applications, such as Financials, Distribution, CRM, and Project Accounting, on a robust and flexible platform. In an interconnected world, Acumatica enables customers to take full control of their businesses, play to their organizations’ unique strengths, and support their clients by following them anywhere on any device.
Acumatica’s culture is casual and high-energy. We are passionate about our product and our mission, and we are loyal to each other and our company. We value work/life balance, efficiency, simplicity, freakishly friendly customer service, and making a difference in the world. Acumatica offers exceptional professional and financial growth potential.
Acumatica is hiring a Machine Learning Engineer for the ML team in Serbia, Belgrade!
Responsibilities:
- Develop, implement, and maintain machine learning models, ensuring they are scalable and performant in a production environment.
- Utilize deep knowledge of traditional machine learning algorithms (e.g., regression, classification, clustering) and generative AI techniques (e.g., GANs, VAEs, transformers) to build innovative solutions.
- Employ various ML tools and frameworks to facilitate the development process, ensuring the use of best practices and state-of-the-art methodologies.
- Work extensively with Python, utilizing libraries such as Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, PyTorch, and Keras to develop and optimize models.
- Apply general software development skills in C# to integrate machine learning solutions within the broader application architecture.
- Design and implement model deployment strategies on cloud platforms such as AWS or Azure, ensuring robust, reliable, and scalable solutions.
- Collaborate with cross-functional teams, including data engineers, product managers, and software developers, to deliver end-to-end machine learning solutions.
- Stay abreast of the latest advancements in machine learning and AI, continuously improving skills and applying new knowledge to ongoing projects.
Requirements:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
- 4+ years of hands-on experience in machine learning engineering, with a proven track record of building and deploying production-grade ML models.
- Proficient in Python, with extensive experience using libraries such as Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, PyTorch, and Keras.
- Solid experience in general software development using C#.
- Demonstrated expertise in deploying machine learning models on AWS or Azure cloud platforms.
- Strong problem-solving skills, with the ability to work independently and as part of a team.
- Excellent communication skills, both written and verbal, with the ability to convey complex technical concepts to non-technical stakeholders.
Good Plus:
- Experience with fine-tuning large language models (LLMs) and working with NLP-related tasks.
- Familiarity with Docker, Kubernetes, and other containerization/orchestration technologies.
What we offer:
- Good relocation package (we help people to relocate to Serbia and handle the whole process)
- Private health insurance
- Performance bonuses
- Good salary
- Full work equipment (Laptop, mouse, headphones, etc)
- Great opportunities for career growth
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture AWS Azure Classification Clustering Computer Science Docker Engineering GANs Generative AI Keras Kubernetes LLMs Machine Learning Mathematics ML models Model deployment NLP NumPy Pandas Python PyTorch Scikit-learn SciPy TensorFlow Transformers
Perks/benefits: Career development Flex hours Gear Health care Relocation support Startup environment
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