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Senior Data and AI Engineer with 16+ years of experience across data engineering, analytics, and AI/ML. Proven track record in building cloud-native data platforms, implementing GenAI solutions, LLMs, and enterprise-scale RAG pipelines. Expert in Snowflake, AWS, and BI tools like Looker and Tableau. Adept at MLOps, DBT, and AI DevOps for deploying scalable, secure, and intelligent systems. Strong leadership in AI projects, enabling business transformation through automation, data-driven decision-making, and next-gen GenAI applications.
Highly accomplished Senior AI/ML Data Scientist with over a decade of expertise in developing, optimizing, and deploying sophisticated machine learning models, deep learning frameworks, and AI-driven solutions. Proficient in designing and implementing advanced predictive analytics, large-scale natural language processing (NLP) architectures, and state-of-the-art computer vision applications. Extensive experience in Python programming, leveraging frameworks such as TensorFlow, PyTorch, Scikit-learn, FastAPI, and Flask for end-to-end AI model development and deployment. Demonstrated expertise in MLOps, CI/CD pipelines, containerization, and cloud-based deployments using AWS, Azure, GCP, Docker, Kubernetes, MLflow, Terraform, and Snowflake.
I’m an AI/ML Consultant with 10+ years of experience delivering end-to-end machine learning solutions across sectors like pharma, energy, insurance, and manufacturing. I specialize in building scalable AI systems including GenAI, computer vision, and edge AI using tools like PyTorch, TensorFlow, Azure, and AWS. As Founder of MLGlow, I’ve led diverse AI projects from R&D to production, helping clients solve real-world problems with cutting-edge technologies. I thrive in fast-paced, collaborative environments focused on innovation and impact.
You might be looking to hire someone to solve a data problem or work on your Python, SQL or C++ project backlog. For over 20 years, I’ve been applying data science and engineering to solve real-life problems faced by both businesses and experimental scientists. Whilst scientific employments were heavy on ML, statistical modelling and data analysis, the employment with the retailer helped me to build contemporary engineering skills. You will hire a professional with a versatile skill set and the experience of working in multidisciplinary teams, who will: • help you find a data-driven solution to your business problem • architect/prototype the solution • implement solution working independently or as part of a team If you wish to discuss your project, let’s arrange a call.
I am Innovative Machine Learning Engineer with 5+ years of experience, including 2+ years of professional expertise in NLP and conversational AI frameworks. Skilled in Machine learning, Deep-learning, LLM/GenAI technologies, cloud platforms, and enterprise-grade software solutions. Proven track record in developing and deploying AI pipelines, optimising data workflows, and delivering actionable insights. Seeking to leverage expertise in machine learning and AI to drive technological advancements and solve complex business challenges.
To be one of the best engineers in the field I'm interested in; to provide people with ecological solutions through original projects; and to contribute to the economy of my country through the defence industry and the energy sector. Also, to implement the projects and develop new technologies that I have noticed throughout my life.
I'm a senior data engineer with a strong track record of designing and optimizing data infrastructure to unlock business value. With deep expertise in Python, SQL, Airflow, and AWS, I’ve led impactful projects—from building ML-powered job classification systems to boosting CRM engagement by 197% and cutting pipeline runtimes by 800%. I thrive in cross-functional environments, bringing analytical rigor, clean engineering practices, and a focus on outcomes. My experience spans startups to established platforms, and I’m passionate about solving complex data challenges that drive real results.
I’m a data scientist and machine learning engineer with 5+ years of experience working on end-to-end ML solutions across industries such as Manufacturing, Energy, Software, among others. My background combines strong statistical analysis, machine learning, and software engineering skills.I’ve built models for predictive analytics, NLP, and computer vision, and have experience deploying them using tools like PyTorch, ONNX, and cloud platforms like GCP & AWS.
I am a results-driven Data Engineer with over 3 years of experience in building scalable ETL/ELT pipelines, optimizing data workflows, and ensuring data accuracy. Proficient in Python, SQL, and big data tools like Spark and Hive, I specialize in designing and implementing cloud-based data systems using AWS and data orchestration using Apache Airflow/Autosys. My expertise includes data modeling, query optimization, and stream processing. I thrive in collaborative, agile environments and am committed to delivering high-quality, reliable data solutions to support data-driven decision-making.
I’m a Data Analyst and Machine Learning enthusiast with 4+ years of experience in data analytics, dashboard development, and database management. Skilled in Python, SQL, Power BI, and machine learning techniques, I’ve worked on real-world projects involving customer segmentation, predictive modeling, and business intelligence. I value clear communication, remote collaboration, and delivering data-driven insights that help clients make smarter decisions.
At Techamana, we maintain the highest standards in developer selection. Our Scikit-learn experts undergo a comprehensive 4-step vetting process that evaluates technical skills, problem-solving abilities, communication skills, and team and culture fit. Only the top 5% of applicants pass our rigorous screening, ensuring you work with exceptional talent who can deliver outstanding results for your projects.
Rigorous coding challenges and problem-solving tests to evaluate Scikit-learn proficiency and best practices.
Thorough examination of past projects and contributions to open-source Scikit-learn repositories to assess real- world experience.
Video responses for open-ended questions to assess problem-solving ability, communication skills, and team and culture fitment.
When hiring a Scikit-learn specialist, look for model selection, feature engineering, and pipeline creation expertise.
Candidates should implement algorithms, tune hyperparameters (GridSearchCV), validate with cross-validation, and integrate models into services or batch pipelines.
Industry insights and best practices
Scikit-learn is a popular Python library for machine learning, providing a wide range of algorithms for classification, regression, clustering, and dimensionality reduction.
Scikit-learn provides various algorithms for classification tasks, such as logistic regression, support vector machines (SVMs), and decision trees.
Scikit-learn provides various algorithms for regression tasks, such as linear regression, support vector regression (SVR), and decision tree regression.
Scikit-learn provides various algorithms for clustering tasks, such as k-means clustering and DBSCAN.
Scikit-learn provides various algorithms for dimensionality reduction tasks, such as principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE).
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