Machine Learning & MLOps Engineer (Remote, US)

We are seeking a highly skilled and experienced Machine Learning & MLOps Engineer to join our dynamic team. The Machine Learning & MLOps Engineer will play a critical role in designing, developing, and deploying machine learning models and systems, as well as implementing MLOps practices and tools to operationalize and automate the machine learning lifecycle.

The ideal candidate will possess deep expertise in machine learning algorithms, frameworks, and tools, as well as experience with MLOps practices such as model deployment, monitoring, and governance.

Key Responsibilities

• Machine Learning Development: Design, develop, and deploy machine learning models and algorithms to solve complex business problems and drive actionable insights from data, using libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, or Apache Spark.


• Data Preparation & Feature Engineering: Gather, preprocess, and transform data from various sources to prepare it for machine learning model training, performing exploratory data analysis (EDA) and feature engineering to extract relevant insights and features.


• Model Training & Evaluation: Train, validate, and optimize machine learning models using appropriate techniques and methodologies, such as cross-validation, hyperparameter tuning, and model selection, to achieve optimal performance and generalization on unseen data.


• MLOps Implementation: Implement MLOps practices and tools to automate and streamline the machine learning lifecycle, including model deployment, monitoring, versioning, and governance, using platforms such as Kubeflow, MLflow, or TFX.


• Infrastructure & DevOps: Collaborate with DevOps and infrastructure teams to design and deploy scalable, reliable, and secure machine learning infrastructure and environments, leveraging cloud services such as AWS, Azure, or Google Cloud Platform.


• Collaboration & Communication: Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to gather requirements, define technical specifications, and deliver high-quality machine learning solutions that meet business objectives.

Qualifications

• Bachelor's degree in Computer Science, Data Science, or a related field; Master's degree or PhD preferred.


• Minimum of 3-5 years of experience in machine learning engineering, with hands-on experience in designing, developing, and deploying machine learning models and systems.


• Deep expertise in machine learning algorithms, frameworks, and libraries such as TensorFlow, PyTorch, scikit-learn, or Apache Spark.


• Experience with MLOps practices and tools, such as Kubeflow, MLflow, TFX, Docker, Kubernetes, or GitLab CI/CD.


• Strong programming skills in languages such as Python, Java, or Scala, as well as experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.


• Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment and communicate technical concepts to non-technical stakeholders.

Join Our Team

If you are a strategic thinker with a passion for driving business transformation in the cloud and technology services space, we invite you to join our team and help shape the future of digital innovation. Apply now and take your career to new heights!