AI/ML Engineer (Generative AI, ML, Data Analytics)

Responsibilities:

We are seeking an experienced AI/ML Engineer who is proficient in Generative AI, Machine Learning, and Data Analytics to join our team. The ideal candidate will not only have strong technical expertise but also excellent communication skills to interact with clients, explain AI concepts in simple terms, and deliver impactful business solutions.
You will work on projects such as building AI chatbots, content automation tools, predictive analytics models, recommendation engines, and business dashboards.

Key Responsibilities:

• Design, develop, and deploy AI-powered solutions across Generative AI, ML, and Data Analytics use cases.
• Fine-tune and deploy LLMs (e.g., GPT, BERT) and integrate APIs (OpenAI, Anthropic, Gemini).
• Build and deploy quick demos and prototypes using tools like Streamlit or Gradio.
• Develop ML models for predictive analytics, recommendation engines, NLP solutions, and computer vision tasks.
• Create interactive dashboards and reports (Power BI, Tableau, Plotly) for business intelligence and decision-making.
• Work with SQL and big data tools (PySpark, Airflow, dbt) to manage data pipelines and processing.
• Collaborate with business teams to understand requirements and map them to AI/ML solutions.
• Document processes, models, and provide knowledge transfer to non-technical stakeholders.

Required Skills & Tech Stack:

1. Generative AI (Gen AI)

• Python (primary language)
• PyTorch / TensorFlow (model training & fine-tuning)
• Hugging Face Transformers (LLMs, BERT, GPT-based models)
• LangChain (building AI agents & pipelines)
• OpenAI API / Anthropic API / Gemini API (chatbots, content generation)
• Stable Diffusion / MidJourney / DALL·E (image generation)
• Gradio / Streamlit (quick demos, prototypes)

2. Machine Learning (ML)

• Python (NumPy, Pandas, Scikit-learn)
• PyTorch / TensorFlow / Keras (deep learning)
• XGBoost, LightGBM, CatBoost (tabular data models)
• OpenCV (computer vision)
• NLTK / SpaCy (NLP pipelines)
• MLflow / Weights & Biases (experiment tracking, model management)

3. Data Analytics

• Python (Pandas, Matplotlib, Seaborn, Plotly)
• SQL (MySQL, PostgreSQL, BigQuery)
• Excel / Google Sheets (client-friendly analytics)
• Tableau / Power BI (BI dashboards)
• Apache Spark / PySpark (big data)
• ETL Tools: Airflow, dbt (workflow automation)

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.
• 3–5 years of professional experience in AI/ML/Data Analytics.
• Proven experience delivering real-world AI projects (chatbots, dashboards, predictive models).
• Strong communication skills able to explain technical concepts to non-technical clients.
• Familiarity with agile workflows, Git, and cloud platforms (AWS, GCP, Azure).

Preferred Certifications (nice to have):

• AWS Certified Machine Learning – Specialty
• Google Cloud Professional Machine Learning Engineer
• Microsoft Certified: AI Engineer Associate
• Tableau / Power BI certifications

Soft Skills

• Strong problem-solving and analytical mindset.
• Ability to work independently and in a collaborative team environment.
• Client-focused, with the ability to translate business needs into technical solutions.
• Excellent written and spoken English.