Artificial Intelligence/Machine Learning Engineer

2 months ago

Bengaluru, India Aceseekers Full time

Location - Bangalore (Hybrid mode of work. 3 days from office)

Experience - 7+Years

Job Description :

- Experience in Part of Speech Tagging - Use several techniques, including table lookups, n-grams, and hidden Markov models, to tag parts of speech in sentences, and compare their performance.

- Machine Translation - Able to build a deep neural network that functions as part of an end-to-end machine translation pipeline. The completed pipeline will accept English text as input and return the French translation.

- Speech Recognizer - Able to build a deep neural network that functions as part of an end-to-end automatic speech recognition (ASR pipeline. The model will convert raw audio into feature representations, which will then turn them into transcribed text.

- Experience in Image Representation & Analysis

- Able to understand how images are represented numerically.

- Implement image processing techniques like color and geometric transforms.

- Program one's own convolutional kernel for object edge-detection.

- Experience in Convolutional NN Layers - Know region-based CNNs, like Faster R-CNN, have allowed for fast, localized object recognition in images. Knowledge in YOLO/single shot object detection system.

- Features & Object Recognition - Able to extract information about an object's color and shape. Use features to identify areas on a face and to recognize the shape of a car or pedestrian on a road.

- Image Segmentation - Implement k-means clustering to break an image up into parts. Find the contours and edges of multiple objects in an image.

- Knowledge to combine CNNs and RNNs to build a complex captioning model.

- Implement an LSTM for caption generation. Ability to train a model to predict captions and understand a visual scene.

- Architect and execute model deployment strategies, harnessing containerization (Docker) and orchestration (Kubernetes) for exceptional scalability and reliability.

- Engineer automated CI/CD pipelines that facilitate seamless model deployment, monitoring, and continuous optimization.

- Define and refine performance benchmarks, and optimize models and infrastructure to achieve peak efficiency, scalability, and robustness.

- Remain at the forefront of industry trends and emerging technologies, expertly integrating the latest advancements into our Client ecosystem.

Requirements :

- 7+ years of experience with a significant focus on developing, deploying & supporting AI solutions in production environments.

- Proven experience in building enterprise software products for B2B businesses

- Solid engineering and coding skills and understanding of data structures, algorithms, and software design principles. Ability to write high performance production quality code in Python

- Proficiency with Client libraries, platforms & frameworks (e.g., PyTorch, scikit-learn).

- Strong expertise in using stat, Client, DL and foundation models

- Strong understanding of AI and machine learning algorithms.

- Experience in deploying AI models in cloud or on-prem environments.

- Experience with MLOps tools (MLFlow) and practices for continuous integration and deployment of Client models using Kubeflow and Kserve.

- Has familiarity with deploying applications on Kubernetes

- Exposure to generative AI models and agent architectures on platforms such as AWS or Azure

- Good to have experience in the GenAI technologies like Prompt Engineering, Azure openAI models like GPT3.5, GPT4, VectorDB, langchain, etc.

- Excellent problem-solving skills and the ability to work independently as well as in a collaborative team environment.

(ref:hirist.tech)

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