Python Developer + Machine Learning and AI experience - Diverse Linx

Job Description

Technical/Functional Skills

Required Qualifications:

Python Development: 6+ years of hands-on experience with Python development and programming, including writing efficient, reusable, and scalable code.

Machine Learning Frameworks: 6 + years of experience in Machine Learning Frameworks such as TensorFlow, PyTorch, Scikit-learn, and Keras.

Natural Language Processing (NLP): Proficient with Natural Language Processing (NLP) libraries and techniques such as NLTK, SpaCy, transformers, and BERT.

Data Manipulation Libraries: Very strong experience with Data Manipulation Libraries such as Pandas, NumPy and Dask for data preprocessing and analysis.

Azure Cloud Services : Experienced with deploying and managing machine learning models on Azure, including familiarity with Azure Machine Learning, Azure

Databricks, and Azure Functions.

Problem-Solving Skills: Ability to tackle complex problems and develop innovative solutions.

Communication Skills: Excellent verbal and written communication skills to effectively collaborate with team members and stakeholders.

Project Experience: Demonstrated experience with real-world projects involving large-scale data and advanced machine learning techniques

API Development: Proficiency in developing and deploying APIs for machine learning models using frameworks like Flask, Fast API, and Django.

Preferred Qualifications:

Educational Background: Bachelor's or master s degree in computer science, Data Science, Machine Learning, Artificial Intelligence, or a related field.

Certifications: Relevant certifications in machine learning, AI, or cloud services (e.g., Microsoft Certified: Azure AI Engineer Associate) is a plus.

Data Engineering Skills: Experience with data engineering tools and frameworks such as Apache Spark, Hadoop, and Kafka.

Big Data Technologies: Familiarity with big data technologies and ecosystems, including Hive, Presto, and HBase.

Reinforcement Learning: Knowledge of reinforcement learning algorithms and frameworks.

MLOps: Familiarity with MLOps practices and tools, including CI/CD for machine learning, model versioning, and monitoring using tools like MLflow, Kubeflow, and TFX.

Containerization and Orchestration: Knowledge of containerization technologies such as Docker and orchestration tools like Kubernetes.

Version Control: Experience with version control systems such as Git and collaborative platforms like GitHub or GitLab.

Visualization Tools: Proficiency with data visualization tools like Matplotlib, Seaborn, Plotly, and libraries such as Dash for building interactive web applications.

Soft Skills: Strong analytical and critical thinking skills, ability to work in a fast-paced environment, and adaptability to new technologies and methodologies.

Publications and Contributions: Contributions to academic journals, conferences, or open-source projects in the fields of machine learning, AI, or data science.

Roles & Responsibilities

Design and architect scalable, secure, and high-performance applications using Python.

Design, develop, and implement advanced machine learning and AI solutions.

Data Preprocessing and analysis: Collect analyze large data sets to ensure data quality and relevance & Implement data cleaning and transformation & augmentation to prepare data for model training and evaluation

Utilize NLP techniques to extract and process textual data.

Work with data manipulation libraries to preprocess and analyze large datasets.

Apply reinforcement learning and other advanced AI techniques where appropriate.

Develop scalable and efficient algorithms for data processing and predictive modeling.

Continuously improve model performance through iterative experimentation and optimization.

Collaborate with cross-functional teams to define and execute data-driven projects.

Deploy and manage machine learning models on Azure.

Stay updated with the latest advancements in machine learning, AI, and data science.