Lead AI Engineer

Job Description
As a Lead Artificial Intelligence Engineer at Leapfrog Technology, you will be at the forefront of shaping the future of data-driven solutions. You'll lead a talented team, drive the development of innovative AI projects, and work collaboratively across functions to turn complex business challenges into actionable insights.

Key Responsibilities

• Leadership Excellence: Lead and inspire a team of AI Engineers and Data Scientists, fostering a culture of innovation, collaboration, and continuous growth.
• End-to-End Ownership: Take full ownership of the AI project lifecycle, from ideation and design to development, deployment, and maintenance.
• Technological Innovation: Explore and assess emerging technologies to enhance the performance, maintainability, and reliability of AI systems.
• Engineering Best Practices: Apply robust software engineering practices to AI, including CI/CD pipelines, automation, and quality assurance.
• Architectural Leadership: Collaborate with technology experts to make informed architectural decisions, and ensure thorough technical documentation.
• Risk Mitigation: Proactively identify and address project risks, conduct root cause analysis, and implement preventive measures.
• Cross-functional Collaboration: Engage closely with cross-functional teams, including business stakeholders, product managers, software engineers, and data engineers, to deliver impactful data-driven solutions.
• Continuous Learning: Stay at the cutting edge of data science, ML, and AI developments, and leverage emerging technologies to solve complex business problems.
• Mentorship and Growth: Coach and motivate team members, identify training needs, and foster their professional development.
• Organizational Excellence: Actively uphold and promote the company's culture, processes, and standards to ensure consistent excellence in our work.

Job requirements

Education And Experience

• A degree (Masters preferred) in Computer Science, Engineering, Artificial Intelligence, Data Science, Applied Mathematics, or related fields.
• Minimum 5+ years of hands-on experience in AI/ML or Data Science, preferably in real industry settings, with a track record of building data products that have positively impacted customer satisfaction and revenue growth.

Technical Skills

• Proficiency in a wide range of Machine Learning techniques and algorithms, with the ability to apply advanced analytics methods, including Bayesian statistics, clustering, text analysis, time series analysis, and neural networks on large-scale datasets.
• Expertise in at least one specialized area of application, such as Computer Vision or Natural Language Processing (NLP). (NLP Expertise preferred)
• Strong programming skills in Python, including expertise in the data ecosystem (Numpy, Scipy, Pandas, etc.) or equivalent skills in languages like R, Java, Scala, or Julia, with a focus on producing production-quality code.
• Hands-on experience with popular ML frameworks like Scikit-Learn, PyTorch, or TensorFlow.
• Expertise with Generative AI and Large Language Models (LLMs) along with their implementation in real-life applications.
• Experience building end-to-end ML systems (MLOps).
• Experience in deploying code in web frameworks such as Flask, FastAPI or Django.
• Experience working in a cloud environment like AWS, Azure, or GCP for ML work.
• Good grasp of SQL/NoSQL databases and scripting skills, particularly within analytics platforms and data warehouses.
• Good grasp of software engineering concepts (SDLC, Version Control, CI/CD, Containerization, Scalability and so on), programming concepts, and tools/platforms like Git and Docker.
• Bonus: Experience with Big Data technologies such as Apache Spark, Kafka, Kinesis, and cloud-based ML platforms like AWS SageMaker or GCP ML Engine.
• Bonus: Experience with data visualization and dashboard tools like Tableau or Power BI.

Soft Skills

• Highly motivated, self-driven, entrepreneurial mindset, and capable of solving complex analytical problems under high-pressure situations.
• Ability to work with cross-functional and cross-regional teams.
• Ability to lead a team of Data/AI professionals and work with senior management, technological experts, and the product team.
• Excellent written and verbal communication skills, comfortable with client communication.
• Good leadership skills - ability to motivate and mentor team members, ability to plan and make sound decisions, ability to negotiate tactfully with the client and team.
• Results-oriented, customer-focused with a passion for resolving tough technical and operational challenges.
• Possess excellent analytical and problem-solving abilities.
• Good documentation skills.
• Experienced with Agile methodologies like Scrum/Kanban

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Questions

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How many years of hands-on experience do you have in AI/ML or Data Science? *

What areas of machine learning are you most proficient in? *

Supervised Learning

Unsupervised Learning

Deep Learning

Reinforcement Learning

NLP

Computer Vision

Others

In which machine learning frameworks do you have working experience? *

TensorFlow

PyTorch

Scikit-learn

XGBoost

JAX

Others

Which traditional machine learning algorithms have you worked with? *

Linear Regression, Logistic Regression

Decision Trees, Random Forest, Gradient Boosting (XGBoost, LightGBM, CatBoost)

SVM (Support Vector Machines)

Clustering (K-Means, DBSCAN, Hierarchical)

Dimensionality Reduction (PCA, t-SNE, UMAP)

Others

Which deep learning architectures have you worked with? *

CNN (Convolutional Neural Networks)

RNN (Recurrent Neural Networks)

LSTM (Long Short-Term Memory)

GRU (Gated Recurrent Units)

Transformers (BERT, GPT, T5, ViT)

GANs (Generative Adversarial Networks)

Others

What cloud platforms have you worked with for ML model deployment? *

AWS

GCP

Azure

Others

Which MLOps tools do you have experience with? *

MLflow

Kubeflo

DVC

Airflow

Others

If offered the position, how soon could you join our company? *

This is not a remote position. Are you fine relocating to Pune? *

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