AI/ML Engineer – Artificial Intelligence & Machine Learning

Job Description

Machine Learning Engineer | RK Infotech LLC

The Tone:
This is a full-time role at RK Infotech LLC, located in Remote / Onsite (Client Requirement – USA). RK Infotech LLC operates within the US IT industry, focusing on Artificial Intelligence & Machine Learning solutions. This position is crucial for Master’s students beginning their professional careers, offering the chance to develop and implement AI/ML models to solve real-world problems for clients and internal projects. The role directly contributes to the expansion of AI/ML capabilities and delivering impactful data-driven solutions.

The TL;DR
• Role: Early Career
• Type: Full-Time (W2)
• Location: Remote, USA
• Mission: This person will be responsible for assisting in the development, training, and evaluation of machine learning models to address real-world problems.
• Tech Stack: Python, Pandas, NumPy, Scikit-learn, SQL, TensorFlow, PyTorch, Keras, Matplotlib, Seaborn, Power BI, Tableau, AWS, Azure, GCP

What You’ll Actually Do
• Develop: Assist in the creation, training, and evaluation of ML/AI models.
• Manage Data: Process large datasets through data preprocessing and feature engineering.
• Implement: Build machine learning algorithms under the guidance of senior team members.
• Support: Aid in model testing, validation, and performance tuning efforts.
• Collaborate: Work with data scientists, engineers, and business teams on client-driven and internal AI/ML projects.

The Must-Haves
• Background: Master’s degree (completed or pursuing) in Data Science, AI, ML, Computer Science, Engineering, or a related field, with a focus on starting a career in Artificial Intelligence & Machine Learning.
• Experience: Entry-level to 5 years of experience, including strong academic projects or internship experience in AI/ML, along with robust programming knowledge in Python.
• Skills: Strong understanding of Machine Learning concepts (supervised, unsupervised, model training/testing, overfitting), knowledge of statistics, probability, and linear algebra. Familiarity with Pandas, NumPy, Scikit-learn, and basic knowledge of SQL and databases.
• Bonus: Academic or internship projects in AI/ML/Data Science, exposure to TensorFlow, PyTorch, or Keras, knowledge of Deep Learning, NLP, or Computer Vision. Experience with data visualization tools (Matplotlib, Seaborn, Power BI, Tableau), Cloud exposure (AWS, Azure, GCP – ML services preferred), Kaggle participation, GitHub projects, or certifications.