Machine Learning Engineer
1 week ago
Consultancy Outfit is a UK-based software solution provider that provides secured and compatible ERP and HRM solutions for an organization, which is a web-based solution for accounting, inventory, sale, purchase, and legal management system
.
Responsibilities:
- Design and implement machine learning (ML) models and algorithms to extract insights from structured and unstructured data.
- Develop end-to-end ML pipelines, including data collection, preprocessing, feature engineering, model training, deployment, and optimization.
- Collaborate with data engineers and software developers to ensure data integrity, scalability, and successful integration of ML solutions into production environments.
- Perform data analysis, exploratory data analysis (EDA), and statistical evaluations to uncover trends, patterns, and relationships within data.
- Build, evaluate, and deploy predictive models, classification/regression algorithms, recommendation systems, and advanced analytics solutions.
- Continuously monitor model performance in production and fine-tune as needed for continuous improvement and business impact.
- Work with Natural Language Processing (NLP) techniques including text classification, named entity recognition (NER), sentiment analysis, topic modeling, and language generation.
- Leverage computer vision techniques (if applicable) including image classification, object detection, and optical character recognition (OCR).
- Familiarity with various AI models such as large language models (LLMs), generative AI, reinforcement learning, and deep learning architectures (e.g., CNNs, RNNs, Transformers).
- Utilize Microsoft Power Tools (Power BI, Power Query, Power Automate) for building dashboards, automating workflows, and creating visual analytics for stakeholders.
- Communicate findings and insights to both technical and non-technical stakeholders through reports, dashboards, visualizations, and presentations.
- Stay updated with the latest research and trends in AI, ML, deep learning, and data science.
- Collaborate with business teams to understand problems, define data-driven strategies, and deliver actionable insights.
Qualifications:
- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Machine Learning, Artificial Intelligence, or a related field.
- Proven experience in data science, ML engineering, or similar roles involving production-grade ML solutions.
- Proficiency in programming languages such as
Python
,
R
, or
Java
. - Hands-on experience with ML frameworks such as
TensorFlow
,
Keras
,
PyTorch
,
Scikit-learn
. - Strong understanding of statistical analysis, data preprocessing techniques, and feature engineering.
- Solid experience in using data analysis libraries and visualization tools such as
Pandas
,
NumPy
,
Matplotlib
,
Seaborn
,
Plotly
. - Experience working with
cloud platforms
(AWS, GCP, or Azure) and big data tools like
Spark
,
Hadoop
,
Databricks
. - Familiarity with
SQL
and
NoSQL
databases for data manipulation and integration. - Exposure to
NLP frameworks
(SpaCy, NLTK, HuggingFace Transformers) and real-world NLP projects. - Knowledge of model evaluation and tuning using metrics like accuracy, precision, recall, F1-score, AUC-ROC.
- Strong familiarity with
Microsoft Power BI
,
Power Automate
, and
Power Query
for dashboarding and workflow automation. - Excellent problem-solving skills, attention to detail, and a structured approach to solving complex challenges.
- Strong communication and interpersonal skills, with the ability to translate complex technical concepts into business-friendly language.
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