AI / Machine Learning Engineer

About the job

AI / Machine Learning Engineer Full-Time Freelance Collaboration | Remote | Project-Based Engagement 1. Overview We are onboarding experienced AI/ML Engineers for long-term freelance collaboration on enterprise technology projects with global clients. This opportunity is intended for professionals interested in working on meaningful AI implementations within international delivery environments while contributing to scalable, real-world solutions. The engagement focuses on long-term project collaboration rather than short-term freelance assignments. Engineers will work closely with distributed teams supporting cloud-native and AI-driven platforms. 2. What You Will Work On • Design and development of machine learning solutions aligned with business use cases. • Building and optimizing data pipelines for model training and inference. • Integration of AI/ML models into production applications using APIs and microservices. • Collaboration with Business Analysts, architects, and engineering teams to translate requirements into technical solutions. • Deployment and monitoring of models in cloud environments. • Improving performance, scalability, and reliability of deployed models. • Participation in technical discussions and solution planning activities. 3. Required Technical Skills • Strong programming experience in Python. • Hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn. • Experience working with data processing libraries including Pandas and NumPy. • Understanding of supervised and unsupervised learning techniques. • Experience implementing or deploying machine learning models in real applications. • Familiarity with REST APIs and system integration concepts. • Experience using version control systems such as Git. • Strong analytical and problem-solving abilities. 4. Preferred Experience • Exposure to Generative AI or Large Language Model applications. • Understanding of Retrieval-Augmented Generation or similar AI workflows. • Experience with vector databases or semantic search technologies. • Cloud platform experience with AWS, Azure, or Google Cloud. • Familiarity with Docker, MLOps practices, or automated deployment pipelines. • Experience working within distributed or microservices-based systems. 5. Soft Skills • Strong English communication skills, both written and verbal, suitable for collaboration with international teams. • Ability to clearly explain technical concepts during discussions with cross-functional stakeholders. • Professional communication and responsiveness in remote work environments. • Self-driven mindset with strong ownership and accountability. • Ability to collaborate effectively within distributed teams across time zones. 6. Engagement Model and Compensation • Engagement type: Full-time freelance collaboration. • Compensation structure: Project-based payment. • Compensation per project ranges between INR 90,000 to INR 150,000 per month, depending on project scope, complexity, and experience level. • Engineers may be assigned multiple projects based on performance and delivery alignment. • Payments are aligned with confirmed project onboarding and active participation. • Opportunity for long-term collaboration based on consistent performance. 7. Ideal Candidate Profile • Interested in long-term collaboration within global delivery environments. • Comfortable working in distributed teams and remote collaboration models. • Motivated to work on practical AI implementations and scalable systems. • Able to manage responsibilities across ongoing project engagements. 8. Work Environment • Fully remote collaboration. • Collaboration with international teams operating in the CST (Central Standard Time) time zone. • Expected availability for overlapping working hours to support coordination and delivery discussions. 9. Application Process Candidates interested in long-term collaboration on global AI initiatives are encouraged to apply or connect to discuss alignment and upcoming project opportunities.

Requirements

• Python
• PyTorch
• TensorFlow
• Scikit-learn
• Pandas
• NumPy
• REST APIs
• Git

Preferred Technologies

• Python
• PyTorch
• TensorFlow
• Scikit-learn
• Pandas
• NumPy
• REST APIs
• Git