We are in search of an experienced Machine Learning Engineer with 3 to 4 years of expertise,

specializing in both machine learning algorithms and engineering integrations. The ideal candidate

will have a strong background in Natural Language Processing (NLP), Computer Vision and a proven

track record in deploying machine learning models at scale.

Responsibilities:

Algorithm Development and NLP:

Design, implement, and optimize machine learning algorithms and models.

Utilize NLP techniques for tasks such as sentiment analysis, named entity recognition, and language translation.

Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.

Data Engineering & Integrations:

Perform data preprocessing and feature engineering to ensure high-quality input for machine learning models.

Work with large datasets, ensuring scalability and efficiency in data processing pipelines.

Collaborate with data engineers to integrate machine learning solutions into existing data infrastructure.

Model Training and Evaluation:

Train, fine-tune, and evaluate machine learning models using state-of-the-art techniques.

Implement and improve model validation and testing strategies.

Deployment and Integration:

Build end to end scalable pipeline for executing the models along with integrations with other systems and applications.

Deploy machine learning models into production environments.

Collaborate with software engineers to integrate models into existing systems and applications.

APIs and System Integration:

• Develop and maintain APIs for seamless integration of machine learning models with other

applications and services.

• Ensure smooth interoperability between machine learning systems and broader engineering

infrastructure.

Continuous Learning:

Stay abreast of the latest developments in machine learning and related fields.

Continuously enhance your skills and knowledge through training and self-directed learning.

Qualifications:

Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field.

3 to 4 years of hands-on experience in machine learning model development and deployment.

Should be able to lead and guide a small team.

Proficiency in programming languages such as Python, and experience with machine learning libraries/frameworks such as TensorFlow/PyTorch.

Strong understanding of machine learning concepts, algorithms, and techniques.

Strong understanding of NLP libraries/frameworks (e.g., NLTK, spaCy, Transformers). In-depth understanding of NLP concepts, including word embeddings, attention mechanisms, and transformer architectures.

Experience with data preprocessing, feature engineering, and working with large datasets.

Demonstrated ability to work in a collaborative team environment and communicate effectively with both technical and non-technical stakeholders.

Experience deploying machine learning models into production is a plus.

Familiarity with cloud platforms (e.g., AWS, Azure, or Google Cloud) is a bonus.