Senior Artificial Intelligence Developer

**Job Title:** Machine Learning SpecialistAt our digital consulting company, we strive to create transformative experiences by leveraging the latest technologies and best practices. We foster an environment of continuous learning and success for our team and clients.We are a fast-growing team of passionate problem-solvers and lifelong learners who tackle complex challenges with confidence. Our diverse team spans the globe, primarily based in Canada and India, and now we're looking to add more talented individuals to join us on this exciting journey.As a key member of our team, you will design, build, deploy, and optimize machine learning/AI solutions across various business problems. The ideal candidate has a strong understanding of the ML lifecycle, from data pre-processing and experimentation to deployment, monitoring, and continuous improvement.Key Responsibilities:Model Development & Experimentation:Build, train, and evaluate machine learning models (classification, regression, clustering, NLP, deep learning).Develop custom models or adapt pre-trained models (transfer learning).Conduct feature engineering, feature selection, and data transformation.Perform hyperparameter tuning using tools like Optuna, Ray Tune, or built-in frameworks.Evaluate model performance using appropriate metrics (AUC, F1, MAE, BLEU, WER, etc.).Data Engineering & Processing:Work with structured and unstructured data (text, images, audio, logs, documents).Build data pipelines using Python, SQL, Spark, Airflow, or similar.Apply data quality checks, deduplication, anomaly detection, and data validation.ML Deployment & MLOps:Deploy models as APIs using FastAPI, Flask, Node, or cloud-native tools.Implement CI/CD pipelines for ML (GitHub Actions, GitLab, Jenkins).Use containerization & orchestration (Docker, Kubernetes).Manage models using MLflow, Vertex AI, SageMaker, Azure ML, or Databricks.Implement automated retraining, model versioning, rollback, and monitoring.Handle inference optimizations (quantization, batching, caching).LLM & GenAI (Preferred but not mandatory):Work with foundation models like GPT, LLaMA, Claude, Mistral, etc.Build RAG pipelines with vector databases (Qdrant, Pinecone, FAISS, Elasticsearch).Prompt engineering and evaluation.Optimize embeddings, context windows, and chunking strategies.Integrate LLMs into production APIs and workflows.Cloud & Infrastructure:Experience with at least one cloud provider (AWS, Azure, GCP).Use managed ML services like:AWS: SageMaker, Lambda, Textract, ComprehendAzure: AI Foundry, Functions, SearchGCP: Vertex AI, Cloud RunManage GPU/CPU compute workloads efficiently.Software Engineering Best Practices:Write clean, modular, well-tested Python code.Maintain repositories adhering to branching, versioning, and code review standards.Use design patterns for scalable ML pipelines.Build internal tools for automation, testing, and monitoring.Cross-functional Collaboration:Work closely with product managers, data engineers, backend engineers, and business analysts.Translate business problems into ML solutions with measurable ROI.Document technical designs, APIs, models, architecture diagrams.Monitoring, Observability & Optimization:Implement model monitoring for data drift, concept drift, performance degradation.Evaluate model reliability, bias, fairness.Implement logging & metrics.Continuously improve model performance and resource usage.Required Skills & Qualifications:Technical Skills:Strong Python skills (NumPy, Pandas, Scikit-learn, PyTorch or TensorFlow).Proficiency in ML algorithms, data structures, and ML system design.Experience with deep learning, especially CNN/RNN/Transformers.Knowledge of LLMs, embeddings, tokenizer concepts (preferred).Strong understanding of vector databases (Qdrant, FAISS, Pinecone).Hands-on experience with REST APIs, microservices, and cloud-native deployment.Familiarity with SQL, NoSQL, and data warehouses (Snowflake/BigQuery/Redshift).MLOps & Infrastructure:Docker, Kubernetes, Terraform (good to have).MLflow or equivalent for experiment tracking.CI/CD automation experience.GPU optimization and parallel processing experience.Soft Skills:Problem-solving abilities:Strong analytical thinking.Logical reasoning and sound judgment.Communication skills:Effective written and verbal communication.Clear explanation of technical concepts to non-technical stakeholders.Collaboration skills:Teamwork and collaboration with cross-functional teams.Proactive communication and conflict resolution.Time management skills:Prioritize tasks effectively.Meet deadlines and manage workload efficiently. Benefits: At our digital consulting company, we embrace diversity, equity, and inclusion in our hiring practices and workplace culture. All qualified applicants receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.Our guiding principles are transparency, resourcefulness, unity, and excellence. These values shape our dynamic environment where innovation, quality, and growth are celebrated.