Instructions To Be Followed Before Applying for the Job:
Read the Job Description: Start by carefully reading the job description. Make sure you understand what the job involves.
Check Your Skills: Compare the skills they're looking for with what you know how to do. Figure out where you're strong and where you might need to learn more.
Check Eligibility Criteria: Look at the qualifications they want, like education and experience. Make sure you have what they're asking for.
Update Your Resume and Cover Letter: Change your resume and cover letter to match the job. Highlight the things that make you a good fit.
Learn About the Company: Take some time to find out about the company you want to work for. Understand what they do and what they care about. This helps you show you're interested in them.
Read the Job Description: Start by carefully reading the job description. Make sure you understand what the job involves.
Check Your Skills: Compare the skills they're looking for with what you know how to do. Figure out where you're strong and where you might need to learn more.
Check Eligibility Criteria: Look at the qualifications they want, like education and experience. Make sure you have what they're asking for.
Update Your Resume and Cover Letter: Change your resume and cover letter to match the job. Highlight the things that make you a good fit.
Learn About the Company: Take some time to find out about the company you want to work for. Understand what they do and what they care about. This helps you show you're interested in them.
Skills:
- A mathematical, statistical and probability inclination and deep understanding of some AI concepts.
- Strong coding skills in Python or any AI language of choice.
- Academic / Industry experience in Computer Vision or NLP and Machine Learning.
- Expertise in Clustering Algorithms such as DBSCAN, K-Mean, and etc
- Expertise in Cross-Modality Knowledge
- Understanding of the usage of Transformer-based Language Models for textual embedding
- Understanding of the usage of Computer Vision Models for image embedding or feature extraction
- High Dimensional Vector Visualizations using PCA, TSNE
- Ability to run experiments scientifically and analyze results.
What you will do:
- Breaks down and understands complex business problems, translating it to a machine learning problem.
- Designs and develops scalable solutions that leverage machine learning and deep learning models to meet enterprise requirements.
- Collaborates with development teams to test and deploy machine learning models.
- Creates metrics to continuously evaluate the performance of machine learning solutions.
- Keeps up with new tools, algorithms and techniques in machine learning and AI to implement them in the organization.
Good to have:
- Knowledge into Auto encoders, Latent semantic analysis (LSA), Latent discriminant analysis (LDA), Principal component analysis (PCA), Kmeans, DBSCAN, mediod algorithms, Kmeans, DBSCAN, mediod algorithms, Fischer Discriminant Analysis (FDA)
Eligibility Criteria:
1)Currently pursuing a Bachelor’s or Master's degree or PhD in computer science or a related discipline with a focus on artificial intelligence, machine learning and computer vision.
Location: Remote