SU M M AR Y	PR O FE SSIO NAL E X PE R IE N CEED U CAT IO NSK IL LSC ER T IF IC AT IO NS	li n ke d in .c o m /in / am an ja in 10 1	
am an ja in 78 1@ gm ail.c o m	+9 1- 8 0 573 3339 3	
A M AN  J A IN
M ac h in e L earn in g E ngin eer	
H ig h ly  m otiv a te d  a n d p ro fe ssio n al M ac h in e l e arn in g E ngin eer w it h  o ve r 4  y e ars  o f e xp erie n ce d  w it h  a
d em on str a te d  h is to ry  o f w ork in g i n  t h e i n fo rm atio n  t e ch n olo gy a n d p ro d uct i n dustr y .  S kille d  i n  D ata	 	
S cie n ce ,  C om pute r V is io n ,  P yth on ,  S ta ts ,  N LP ,  S Q L a n d G en era tiv e  A I.  S tr o n g e n gin eerin g p ro fe ssio n al	 	
w it h  a  B ac h elo r o f T ech n olo gy-B T ech  f o cu se d  o n  C om pute r S cie n ce  &amp;  E ngin eerin g.	
Lok su n  T ech no lo g ie s,  B eng alu ru	 	
M an ufa ctu rin g D efe cts  &amp;  Q A I n sp ectio n  w it h  S im il a rit y  b ase d
alg orit h m .( P ate n t i n  p ro g re ss:  U S)
D esig n ,  d eve lo p  a n d d ep lo ye d  A uto m ate  M eetin g c o n ve rs a tio n  f r o m
sp eech  t o  t e x t u sin g S p eake r D ia riz a tio n  a n d t r a n sc rib e.
D esig n ,  D eve lo p  a n d D ep lo ye d  C on ve rs a tio n  S u m mariz a tio n  u sin g	  	
L Lam a-3  ( L LM ) a n d d ep lo ye d  o n  A W S.
 O bje ct D ete ctio n :  D ete ctio n  o f P PE e q u ip m en t f r o m  v id eo  a n d
pro vid in g d ata  w it h  a ll t h e A naly sis  u sin g Y olo .
D esig n ,  d eve lo p  a n d I m ple m en t F ace  R eco g n it io n  u sin g M ob il e  F ace
N et f o r e d ge d evic e s l ik e  m ob il e  P hon e e tc .
D ata  s c ie n ce  m od el t o  p re d ic t c h an ce s o f w in nin g a  p arty  u sin g D ata
A naly sis  a n d M ach in e l e arn in g.
fin etu n ed  L arg e L an gu ag e M od els  o n  A W S c lo u d o n  c u sto m  D ata se t
u sin g Q uan tiz a tio n  a n d f in etu n in g A lg orit h m s.
L ead in g a  T eam  o f 1 0 p eo p le s i n clu din g M L e n gin eers  a n d F u ll s ta ck
d eve lo p ers	
G re enT ech  I T S  L LP,  D elh i	
D esig n ,  d eve lo p  a n d d ep lo ye d  T ra ffic  f lo w  A naly sis :  B uil d  M ult ip le
t r a ffic  a n aly sis  t o ols  f o r m ult ip le  s c e n ario  i n  t o ll m an ag em en t f r o m
sc ra tc h .
V id eo  I n cid en t D ete ctio n  S yste m :  D ete ct A ccid en ts ,  F ir e ,  s m oke ,
W ro n g s id e v e h ic le s,  s to p  v e h ic le s e tc .
W ork in g o n  C om pan y P ro d u ct r e la te d  t o  C om pute r v is io n  a n d
desig n in g a lg orit h m  a n d t r a in in g D eep  L earn in g m od els  a n d L LM s.
C on du cte d  r e se arc h  a n d p re p are d  r e p orts  o n  v a rio u s t o p ic s r e la te d  t o
th e c o m pan y&#039;s  o p era tio n s a n d i n du str y  t r e n ds i n  m ach in e l e arn in g
D om ain  l ik e  O CR ,  P atte rn  R eco g n it io n .	
I sh ir  T ech no lo g ie s,  N oid a	
Part o f a  T eam  o f D ata  S cie n tis ts ,  w ork e d  o n  v a rio u s M L a n d
C om pute r V is io n  A pplic a tio n s a n d W ork e d  o n  M ach in e L  e arn in g L if e
C ycle  l ik e  D ata  G ath erin g,  D ata  p re p ara tio n ,  D ata  P re  p ro ce ssin g,
Exp lo ra to ry  D ata  A naly sis ,  M od e t r a in in g.
M an ag e S erv e r D ata b ase s u sin g S Q L S erv e r M an ag em en t S yste m  a n d
ap ply  v a rio u s T ech niq u es l ik e  D ata  R ep lic a tio n ,  D ata  B ack u p ,  D ata
C lu ste rin g.	
B .  T ech  i n  C om pute r S cie n ce	                       	2 0 15 -2 0 19	
C G PA	 :  7 .7 6 / 10	
P yth on
M ach in e L earn in g	 	
D eep  L earn in g
C om pu te r V is io n	 	
P re d ic tiv e A naly tic s	 	
N LP
D ata  S cie n ce	 	
A W S C lo u d	 	
Larg e L an gu ag e m od el,  G en era tiv e A I
SQ L ,N O S Q L,  P in e C on e,  c h ro m a
Lan g C hain ,  l la m a i n dex
P yto rc h ,  T en so rflo w	  	
J a v aS crip t,  H TM L	 	
Pro m pt E n gin eerin g
M ach in e l e arn in g O pera tio n s ( M LO ps)
D ata  S cie n ce  W it h  P yth on  o n  S im pli le arn .
B ig  D ata  H ad oop  a n d S p ark  d eve lo p er
tr a in in g o n  S im pile arn .
 M aste rin g D ata  S tr u ctu re  a n d A lg o rit h m s
usin g C  a n d C ++.	
M ach in e L earn in g E n gin eerC om pu te r V is io n  E n gin eerD ata B ase  A dm in is tr a to r I n te rnT eerth an ker M ah av eer U niv ers it y	g it h ub.c o m /D ark aid o	M AY  2 0 22 -  P R ESE N TAU G  2 0 21 -  M AY  2 0 22	 	F E B  2 0 20  -  F E B  2 0 21