Remote Senior Machine Learning Engineer

Description:

• IT Labs is seeking a Senior Machine Learning Engineer who is passionate about innovation and creating impactful AI solutions.
• The role involves designing and implementing machine learning models and algorithms for various applications such as classification, regression, clustering, NLP, computer vision, and recommendation systems.
• Responsibilities include optimizing model performance for high accuracy, efficiency, and scalability, as well as working with large datasets to extract insights and develop features.
• The engineer will develop and automate data preprocessing pipelines to ensure data quality and consistency.
• Building scalable and reliable machine learning pipelines and deploying models into production using MLOps principles is a key part of the job.
• The role also requires developing APIs and interfaces to integrate machine learning solutions into existing systems.
• Monitoring the performance of deployed models and pipelines, addressing drift or performance issues, and implementing automated tools for model retraining are essential tasks.
• Staying updated on the latest machine learning tools, technologies, and research to recommend and implement improvements is expected.
• The position requires strong analytical and problem-solving abilities, excellent communication skills, and a collaborative mindset focused on teamwork and knowledge sharing.

Requirements:

• A minimum of 7 years of experience in a Machine Learning Engineering role with demonstrated expertise in designing, deploying, and optimizing scalable machine learning models and systems is required.
• Proficiency in Python is preferred for machine learning development.
• Expertise in ML frameworks such as TensorFlow, PyTorch, or Scikit-learn is necessary.
• Strong knowledge of data manipulation libraries (e.g., Pandas, NumPy) and distributed data processing tools (e.g., Apache Spark) is essential.
• Experience with relational databases (e.g., SQL) and NoSQL databases (e.g., MongoDB) is required.
• A deep understanding of supervised and unsupervised learning techniques is necessary.
• Experience with NLP, computer vision, or time-series analysis is a plus.
• Familiarity with tools and platforms like Docker, Kubernetes, MLflow, and Airflow for managing ML pipelines is expected.
• Experience deploying models on cloud platforms such as AWS, Azure, or GCP is required.
• Proficiency with Git for version control and experience with CI/CD pipelines for automated deployment is necessary.
• Hands-on experience with cloud-based ML tools such as AWS SageMaker, Google Vertex AI, or Azure Machine Learning is required.

Benefits:

• Employees can choose their contract type: Contract or B2B.
• There is an unlimited working-from-anywhere policy.
• Employees receive 10 days of paid time off (PTO) after 4 months of working at IT Labs.
• Referral bonuses are available.
• The position involves working on international projects.
• Employees can participate in virtual knowledge sharing sessions, events, and team hangouts.